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Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

BES_ESnet_Cover_CR  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Requirements Network Requirements Report of the Basic Energy Sciences Network Requirements Workshop Conducted September 22 and 23, 2010 ESnet Energy Sciences Network 2 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name,

2

Energy Sciences Network (ESnet)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages

ESnet ESnet ESnet ESnet ESnet ESnet » MyESnet search... Go Home Network Overview Tools Peering Information Interactive Network Map Network Maps Connected Sites Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) DOE Grids Service Transition R&D Overview 100G Testbed Virtual Circuits (OSCARS) Performance (perfSONAR) Tools Development Green Networking Authentication & Trust Federation (ATF) Partnerships News & Publications ESnet in the News ESnet News Publications and Presentations Galleries ESnet Awards and Honors About ESnet Overview ESnet Staff Governance Our Network Case Studies ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Careers Contact Us

3

ESnet: a Production IPv6 Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services IPv6 Network Engineering Services The Network OSCARS Fasterdata...

4

ESnet Network Measurement Current Status  

E-Print Network [OSTI]

1 ESnet Network Measurement Current Status Joe Metzger Jan 24th 2008 ESCC meeting Energy SciencesSONAR collaboration focused on dynamic hybrid network issues ­ publication, visualization, and analysis of dynamic Architecture ­ Protocols based on the Open Grid Forum Network Measurement Working Group Schemas · Several

5

BES Science Network Requirements  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

the Basic Energy Sciences Network Requirements Workshop Conducted June 4-5, 2007 BES Science Network Requirements Workshop Basic Energy Sciences Program Office, DOE Office of...

6

ESnet  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Research PI Meeting Network Research PI Meeting September 28, 2005 ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) Chin Guok (chin@es.net) ESnet Network Engineer David Robertson (dwrobertson@lbl.gov) DSD Computer Software Engineer Lawrence Berkeley National Laboratory 2 Virtual Circuit Network Service * Every requirements workshop involving the science community has put bandwidth-on-demand as the highest priority - e.g. for o Massive data transfers for collaborative analysis of experiment data o Real-time data analysis for remote instruments o Control channels for remote instruments o Deadline scheduling for data transfers o "Smooth" interconnection for complex Grid workflows New network services are critical for ESnet to meet the need of large-scale science like LHC.

7

Authorizations to Operate for the Energy Sciences Network Enclave (ESnet)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

About ESnet » Governance » Authorizations to Operate for the About ESnet » Governance » Authorizations to Operate for the Energy Sciences Network Enclave (ESnet) About ESnet Overview ESnet Staff Governance ESnet Acceptable Use Policy Site Coordinators Authorizations to Operate for the Energy Sciences Network Enclave (ESnet) Policy Board Our Network Case Studies ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Authorizations to Operate for the Energy Sciences Network Enclave (ESnet) The following letters include Lawrence Berkeley National Laboratory Authority to Operate the Energy Sciences Network Enclave (ESnet) from the

8

BES Science Network Requirements  

E-Print Network [OSTI]

the Directors of the Office of Science, Office of AdvancedOffice of Basic Energy Sciences. This is LBNL report LBNL-BES Science Network Requirements Report of the Basic Energy

Dart, Eli

2011-01-01T23:59:59.000Z

9

ESnet  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

QUILT QUILT May 15-16, 2006 Chin Guok (chin@es.net) ESnet Network Engineer David Robertson (dwrobertson@lbl.gov) DSD Computer Software Engineer Lawrence Berkeley National Laboratory 1 2 Outline Requirements for Virtual Circuit Services Virtual Circuit Characteristics Virtual Circuit Service Functional Requirements Environment of Science is Inherently Multi-Domain Inter-Domain Virtual Circuit Requirements OSCARS: Guaranteed Bandwidth VC Service for SC Science ESnet Virtual Circuit Service Roadmap 3 Requirements for Virtual Circuit Services * Identified as one of the two most important new network service by the 2002 science requirements workshop (#5b-1) (the other being end-to-end performance monitoring) * Intended to address specific science needs 4 Virtual Circuit Characteristics

10

ESnet Policy Board  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet Policy Board About ESnet Our Mission The Network ESnet History Governance & Policies ESnet Policy Board ESCC Acceptable Use Policy Facility Data Policy Career Opportunities...

11

Building A Science DMZ Eli Dart, Network Engineer ESnet Network...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

A Science DMZ Eli Dart, Network Engineer ESnet Network Engineering Group Joint Techs, Winter 2013 Honolulu, HI January 13, 2013 Lawrence Berkeley National Laboratory U.S....

12

ESnet IPv6 History  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

History Engineering Services The Network OSCARS Fasterdata IPv6 Network IPv6 Implementation Checklist ESnet IPv6 Mirror Servers ESnet IPv6 History ESnet supports Sandia and APNIC...

13

ESnet Support for WAN Data Movement Eli Dart, Network Engineer  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Support for WAN Data Movement Eli Dart, Network Engineer ESnet Science Engagement Group Joint Facilities User Forum on Data Intensive Computing Oakland, CA June 16, 2014 Lawrence...

14

The ESnet Engineering Team  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services The ESnet Engineering Team Engineering Services The Network OSCARS...

15

ESnet: Advanced Networking for Science  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Similarly, the experiment facilities at the new Spallation Neu- tron Source and Magnetic Fusion Energy facili- ties will start using the network in ways that require...

16

ESnet IPv6 Mirror Servers  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Mirror Servers Engineering Services The Network OSCARS Fasterdata IPv6 Network IPv6 Implementation Checklist ESnet IPv6 Mirror Servers ESnet IPv6 History ESnet supports Sandia and...

17

ESnet History  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

(Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net ESnet History View ESnet's 25-year anniversary timeline in...

18

Energy Sciences Network (ESnet) | U.S. DOE Office of Science...  

Office of Science (SC) Website

Bookmarks External link Email a Friend Email link to: send Additional Information ESnet Web Site 25 Years ESnet - 25 Years ESnet Celebrates 25 Years ESnet Topology Map ESnet...

19

ESnet OID Registry  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet OID Registry ESnet OID Registry Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net ESnet OID Registry # $Id: ESnet-oid-list,v 1.16 2009/03/11 22:16:11 helm Exp $ # # ESnet OIDs esnet: ansi.113612 esnet: 1.2.840.113612 # # This arc is tracked here: # [Formerly: http://asn1.elibel.tm.fr/cgi-bin/oid/display?oid=1.2.840.113612] # http://www.oid-info.com/get/1.2.840.113612 # Please report any discrepancies to trouble@es.net

20

ESnet4:  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet4: ESnet4: Networking for the Future of DOE Science William E. Johnston ESnet Department Head and Senior Scientist wej@es.net, www.es.net This talk is available at www.es.net/ESnet4 Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the Future of Science Office of Science, Science Programs Requirements Workshops: Nuclear Physics May, 2008 2 DOE's Office of Science: Enabling Large-Scale Science * The Office of Science (SC) is the single largest supporter of basic research in the physical sciences in the United States, ... providing more than 40 percent of total funding ... for the Nation's research programs in high-energy physics, nuclear physics, and fusion energy sciences. (http://www.science.doe.gov) - SC funds 25,000 PhDs and PostDocs

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

ESnet in the News  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

far beyond that," says secretary of energy Steven Chu. Author(s): ESnet Offers National Dark Fiber Network to Greentouch | ESnet Marks 25 Years of Service to Science November 8,...

22

ESnet Planning, Status,  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet Planning, Status, ESnet Planning, Status, and Future Issues William E. Johnston, ESnet Department Head and Senior Scientist Joe Burrescia, General Manager Mike Collins, Chin Guok, and Eli Dart, Engineering Brian Tierney, Advanced Development Jim Gagliardi, Operations and Deployment Stan Kluz, Infrastructure and ECS Mike Helm, Federated Trust Dan Peterson, Security Officer Gizella Kapus, Business Manager and the rest of the ESnet Team wej@es.net, this talk is available at www.es.net Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the Future of Science ASCAC, August 2008 2 DOE Office of Science and ESnet - the ESnet Mission * ESnet is an Office of Science ("SC") facility in the Office of Advanced Scientific Computing Research ("ASCR")

23

Energy Sciences Network (ESnet) | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

Energy Energy Sciences Network (ESnet) Advanced Scientific Computing Research (ASCR) ASCR Home About Research Facilities Accessing ASCR Supercomputers Oak Ridge Leadership Computing Facility (OLCF) Argonne Leadership Computing Facility (ALCF) National Energy Research Scientific Computing Center (NERSC) Energy Sciences Network (ESnet) Research & Evaluation Prototypes (REP) Innovative & Novel Computational Impact on Theory and Experiment (INCITE) ASCR Leadership Computing Challenge (ALCC) Science Highlights Benefits of ASCR Funding Opportunities Advanced Scientific Computing Advisory Committee (ASCAC) News & Resources Contact Information Advanced Scientific Computing Research U.S. Department of Energy SC-21/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-7486 F: (301)

24

ESnet Update  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet Update ESnet Update Winter 2008 Joint Techs Workshop Joe Burrescia ESnet General Manager January 21, 2008 Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the Future of Science 2 TWC SNLL YUCCA MT PNNL LIGO I N E E L LANL SNLA Allied Signal ARM KCP NOAA OSTI ORAU SRS JLAB PPPL Lab DC Offices MIT ANL BNL FNAL AMES N R E L LLNL GA DOE-ALB OSC GTN NNSA International (high speed) 10 Gb/s SDN core 10G/s IP core 2.5 Gb/s IP core MAN rings (≥ 10 G/s) Lab supplied links OC12 ATM (622 Mb/s) OC12 / GigEthernet OC3 (155 Mb/s) 45 Mb/s and less NNSA Sponsored (12) Joint Sponsored (3) Other Sponsored (NSF LIGO, NOAA) Laboratory Sponsored (6) 42 end user sites SINet (Japan) Russia (BINP) CA*net4 France GLORIAD (Russia, China) Korea (Kreonet2

25

ESnet_Cover_New  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Science Network Science Network Requirements Office of Advanced Scientific Computing Research Network Requirements Workshop Conducted April 15 and 16, 2009 Final Report ASCR Network Requirements Workshop Office of Advanced Scientific Computing Research, DOE Office of Science Energy Sciences Network Gaithersburg, MD - April 15 and 16, 2009 ESnet is funded by the US Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR). Vince Dattoria is the ESnet Program Manager. ESnet is operated by Lawrence Berkeley National Laboratory, which is operated by the University of California for the US Department of Energy under contract DE-AC02-05CH11231. This work was supported by the Directors of the Office of Science, Office of Advanced

26

And the OSCARS Goes to ESnet!  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

And the OSCARS Goes to ESnet! And the OSCARS Goes to ESnet! News & Publications ESnet in the News ESnet News Media & Press Publications and Presentations Galleries ESnet Awards and Honors Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net And the OSCARS Goes to ESnet! Interview With Greg Bell, on Real-World 100G Multi-Layer SDN November 1, 2013 | Tags: OSCARS, Solenoidal Tracker at RHIC (STAR) This interview by Roy Chua was originally published on SDN Central website. GRBell-headshot.jpg Greg Bell Greg Bell is director of the Scientific Networking Division at Lawrence Berkeley National Laboratory (Berkeley Lab) in California, and director of

27

ESnet in the News  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Author(s): ESnet Offers National Dark Fiber Network to Greentouch | Author(s): ESnet Offers National Dark Fiber Network to Greentouch | Source: Network World | Berkeley Lab and Internet2 consortium launch world's fastest network July 14, 2011 | Author(s): Bob Brewin | Source: Nextgov | Lawrence Berkeley National Laboratory and the Internet2 consortium plan to build a blistering fast network for the Energy Department that can transmit data at the rate of 100 gigabits per second to support scientific research. ... 100G Ethernet to power Department of Energy network July 14, 2011 | Author(s): Bob Brown | Source: Network World | ‎A new national 100Gbps prototype network being built for the Department of Energy will provide about a tenfold increase in speed for labs doing research together on topics such as clean energy and climate ...

28

ESnet in the News  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Energy Research Network Reaches 100 Gbps Energy Research Network Reaches 100 Gbps October 16, 2012 | Author(s): Ariel Bleicher | Source: IEEE Spectrum | Writing in the October issue of IEEE Spectrum, Ariel Bleicher describes the science drivers behind ESnet's move to a 100 gigabit-per-second network. "When the new 100-gigabit-per-second Energy Sciences Network (ESnet) goes live next month, it will be the world's fastest continent-spanning science network. But this distinction will probably be temporary: Research networks around the world are in the midst of their own big upgrades," wrote Bleicher. "Now more than ever, science depends on the ability to quickly and reliably move massive amounts of data over great distances. Breakthrough predictions and discoveries, such as climate change and

29

ESnet supports Sandia and APNIC IPv6 Background Radiation research  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

supports Sandia and APNIC IPv6 Background Radiation research Engineering Services The Network OSCARS Fasterdata IPv6 Network IPv6 Implementation Checklist ESnet IPv6 Mirror Servers...

30

Network Policies  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Acceptable Use Policy About ESnet Our Mission The Network ESnet History Governance & Policies ESnet Policy Board ESCC Acceptable Use Policy Facility Data Policy Career...

31

ESnet Defined: Challenges and Overview Department of Energy...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Circuits Landscape Summer 2010 ESCC Meeting Columbus, OH Evangelos Chaniotakis, ESnet Network Engineer Lawrence Berkeley National Lab 2 Lawrence Berkeley National Laboratory U.S....

32

ESnet Policy Board  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet Policy Board Larry Smarr Jagdeep Singh Kristin Rauschenbach Cees de Laat David Foster David Clark Vinton Cerf ESCC Acceptable Use Policy Facility Data Policy Career...

33

ESnet4_USA_Map_V2  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Network Requirements Report of the Nuclear Physics Network Requirements Workshop Conducted May 6 and 7, 2008 Nuclear Physics Network Requirements Workshop Nuclear Physics Program Office, DOE Office of Science Energy Sciences Network Bethesda, MD - May 6 and 7, 2008 ESnet is funded by the US Department of Energy, Office of Science, Advanced Scientific Computing Research (ASCR) program. Vince Dattoria is the ESnet Program Manager. ESnet is operated by Lawrence Berkeley National Laboratory, which is operated by the University of California for the US Department of Energy under contract DE-AC02-05CH11231. This work was supported by the Directors of the Office of Science, Office of Advanced Scientific Computing Research, Facilities Division, and the Office of Nuclear Physics.

34

ESnet's On-Demand Bandwidth Reservation Service Wins R&D 100 Award  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet's On-Demand Bandwidth ESnet's On-Demand Bandwidth Reservation Service Wins R&D 100 Award News & Publications ESnet in the News ESnet News Media & Press Publications and Presentations Galleries ESnet Awards and Honors Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net ESnet's On-Demand Bandwidth Reservation Service Wins R&D 100 Award OSCARS Honored with "Oscar of Innovation" July 8, 2013 Contact: Jon Bashor, 510-486-5849, jbashor@lbl.gov RD100 OSCARS 0.6 was recognized as one of R&D Magazine's top 100 technologies. Widely recognized as a mark of excellence, the R&D 100 Awards are the only

35

Historical Network Maps  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services The Network Network Maps Historical Network Maps Engineering...

36

ESxSNMP: ESnet eXtensible SNMP System  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESxSNMP: ESxSNMP: ESnet eXtensible SNMP System Jon Dugan Summer JointTechs 2010, Columbus, OH Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science ESnet Statistics Overview ESxSNMP (Data Collection) Graphite (Visualization) Analytics (Custom Reports) Net Almanac (Metadata) Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science Why another SNMP collection system? Desire to retain raw, unmolested data * Disk is cheap * At least one application in ESnet needs raw data * Aids in troubleshooting of erroneous statistics Automatically detect changes in the network * New interfaces are detected within minutes (tunable) * Dynamic circuits make this especially important Metadata

37

Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Site Feedback: info@es.net About ESnet A Nationwide Platform for Science Discovery The Energy Sciences Network (ESnet) is a high-performance, unclassified national network built to...

38

Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Network Facts & Stats Engineering Services The Network Network Maps Network Facts & Stats Connected Sites Peering Connections ESnet Site Availabiliy OSCARS Fasterdata...

39

ESnet, Orange Silicon Valley, and Bay Microsystems Demonstrate...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet, Orange Silicon Valley, and Bay Microsystems Demonstrate the World's First Long Distance 40Gbps RDMA Data Transfer News & Publications ESnet in the News ESnet News Media &...

40

ESnet: Large-Scale Science and Data Management ( (LBNL Summer Lecture Series)  

ScienceCinema (OSTI)

Summer Lecture Series 2004: Bill Johnston of Berkeley Lab's Computing Sciences is a distinguished networking and computing researcher. He managed the Energy Sciences Network (ESnet), a leading-edge, high-bandwidth network funded by DOE's Office of Science. Used for everything from videoconferencing to climate modeling, and flexible enough to accommodate a wide variety of data-intensive applications and services, ESNet's traffic volume is doubling every year and currently surpasses 200 terabytes per month.

Johnston, Bill

2011-04-28T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

ESnet 4 Helps Researchers Seeking the Origins of Matter | U.S. DOE Office  

Office of Science (SC) Website

Energy Energy Sciences Network (ESnet) » ESnet 4 Helps Researchers Seeking the Origins of Matter Advanced Scientific Computing Research (ASCR) ASCR Home About Research Facilities Accessing ASCR Supercomputers Oak Ridge Leadership Computing Facility (OLCF) Argonne Leadership Computing Facility (ALCF) National Energy Research Scientific Computing Center (NERSC) Energy Sciences Network (ESnet) Research & Evaluation Prototypes (REP) Innovative & Novel Computational Impact on Theory and Experiment (INCITE) ASCR Leadership Computing Challenge (ALCC) Science Highlights Benefits of ASCR Funding Opportunities Advanced Scientific Computing Advisory Committee (ASCAC) News & Resources Contact Information Advanced Scientific Computing Research U.S. Department of Energy SC-21/Germantown Building

42

25420_ESNet_ASCR_Cover_Final2  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Requirements Network Requirements ASCR Network Requirements Review Final Report Conducted October 4-5, 2012 ESnet Energy Sciences Network DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or

43

26094_ESNet_BER_Cover_052213  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and Environmental Research Network Requirements and Environmental Research Network Requirements BER Network Requirements Review Final Report Conducted November 29-30, 2012 ESnet Energy Sciences Network DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or

44

BER_ESnet_Cover_WhiteBckgrnd  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Requirements Network Requirements Report of the Biological and Environmental Research Network Requirements Workshop Conducted April 29-30, 2010 ESnet Energy Sciences Network DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name,

45

ESnet Organizational Chart  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Deployment Office of the CTO Revised 10162013 Special Projects Denise Sumikawa Network Engineering Michael Bennett Audio, Video, Data Collaboration Advanced Network Technologies...

46

The Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Engineering Services The Network Network Maps Network Facts & Stats Connected Sites Peering Connections ESnet Site Availabiliy OSCARS Fasterdata IPv6 Network Network...

47

ESnet in the News  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

today announced plans to build an advanced research network for the Department of Energy as part of an effort to spur U.S. scientific advancement. The network, which is being...

48

ESnet Marks 25 Years of Service to Science  

SciTech Connect (OSTI)

More information: http://www.es.net/news-and-publications/esnet-news/2011/esnet-celebrates-25th-anniversary-at-sc11/

None

2011-01-01T23:59:59.000Z

49

ESnet Extends 100G Connectivity Across Atlantic  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and universities ultra-fast access to scientific data from the Large Hadron Collider (LHC) and other research sites in Europe. ESnet's transatlantic extension will deliver a...

50

BES Workshop Reports  

Office of Science (SC) Website

Resources » Resources » Reports Basic Energy Sciences (BES) BES Home About Research Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Program Summaries Brochures Reports Abstracts Accomplishments Presentations BES and Congress Science for Energy Flow Seeing Matter Scale of Things Chart Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » News & Resources Reports Print Text Size: A A A RSS Feeds FeedbackShare Page Provided below is a listing of BES workshop reports that address the status of some important research areas that are used to help identify research

51

Network Maps  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Network R&D Overview Experimental Network Testbeds Performance (perfSONAR) Software & Tools...

52

Essential Role in Modern Science William E. Johnston, ESnet Adviser and Senior Scientist  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Evolution of Research and Evolution of Research and Education Networks and their Essential Role in Modern Science William E. Johnston, ESnet Adviser and Senior Scientist Chin Guok, Evangelos Chaniotakis, Kevin Oberman, Eli Dart, Joe Metzger and Mike O'Conner, Core Engineering, Brian Tierney, Advanced Development, Mike Helm and Dhiva Muruganantham, Federated Trust Steve Cotter, Department Head wej@es.net, this talk is available at www.es.net Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the Future of Science TERENA Networking Conference 2009 2 DOE Office of Science and ESnet - the ESnet Mission * The Office of Science (SC) is the single largest supporter of basic research in the physical sciences in the United States, providing more than 40 percent of total funding for US research programs in high-energy

53

BES Science Network Requirements  

E-Print Network [OSTI]

the Directors of the Office of Science, Office of AdvancedBasic Energy Sciences, DOE Office of Science Energy SciencesDepartment of Energy, Office of Science, Office of Advanced

Dart, Eli

2011-01-01T23:59:59.000Z

54

BES Science Network Requirements  

E-Print Network [OSTI]

in computational nanoscience, providing opportunities toby the needs of users in nanoscience research. The internalprogram and the broader nanoscience community. To understand

Dart, Eli

2011-01-01T23:59:59.000Z

55

BES Science Network Requirements  

E-Print Network [OSTI]

2 years) Electronic structure calculations, quantum many-periodic electronic structure calculations for heteroatomwe do an electronic structure calculation on Franklin to

Dart, Eli

2011-01-01T23:59:59.000Z

56

ESnet 2009 Excellence Gov Award Winner | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

Energy Energy Sciences Network (ESnet) » 2009 Excellence Gov Award Winner Advanced Scientific Computing Research (ASCR) ASCR Home About Research Facilities Accessing ASCR Supercomputers Oak Ridge Leadership Computing Facility (OLCF) Argonne Leadership Computing Facility (ALCF) National Energy Research Scientific Computing Center (NERSC) Energy Sciences Network (ESnet) Research & Evaluation Prototypes (REP) Innovative & Novel Computational Impact on Theory and Experiment (INCITE) ASCR Leadership Computing Challenge (ALCC) Science Highlights Benefits of ASCR Funding Opportunities Advanced Scientific Computing Advisory Committee (ASCAC) News & Resources Contact Information Advanced Scientific Computing Research U.S. Department of Energy SC-21/Germantown Building

57

ESnet Update Steve Cotter, Dept Head Lawrence Berkeley National Lab  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Update Update Steve Cotter, Dept Head Lawrence Berkeley National Lab Winter 2011 Joint Techs Clemson, SC Feb 2, 2011 Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science @ESnet: It's all about the Science * More bandwidth to DOE facilities and Labs at lower costs * Richer network services in support of distributed science - Develop 'network aware' integrated services that deliver 'end-to-end' high- performance data transfer, HPC/cloud computing, and science collaborative services * Carrier-class network operations providing high network availability to all DOE facilities - Seamless network interoperability across multiple network domains * Develop and deploy energy-aware and efficient networking infrastructure * Provide a networking research testbed for DOE community

58

ESnet Defined: Challenges and Overview Department of Energy Lehman Review of ESnet February 21-23, 2006  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Networking for the Future of Science Networking for the Future of Science ESnet4: Networking for the Future of DOE Science Joe Metzger Senior Engineer metzger@es.net, www.es.net Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the Future of Science International ICFA Workshop on Digital Divide Issues for Global e-Science October 25, 2007 2 DOE's Office of Science: Enabling Large-Scale Science * The Office of Science (SC) is the single largest supporter of basic research in the physical sciences in the United States, ... providing more than 40 percent of total funding ... for the Nation's research programs in high-energy physics, nuclear physics, and fusion energy sciences. (http://www.science.doe.gov) - SC funds 25,000 PhDs and PostDocs * A primary mission of SC's National Labs is to build and operate very

59

24052_NP_ESnet_Cover_150_v3  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Requirements Network Requirements Report of the Nuclear Physics Network Requirements Workshop Conducted August 25 and 26, 2011 ESnet Energy Sciences Network 2 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade

60

BES Budget | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

Budget Basic Energy Sciences (BES) BES Home About Staff Organization Chart .pdf file (46KB) BES Budget BES Committees of Visitors Directions Jobs Organizational History Research...

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61

BES Funding Opportunities | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

BES Funding Opportunities BES Funding Opportunities Materials Sciences and Engineering (MSE) Division MSE Home About Research Areas Energy Frontier Research Centers (EFRCs) DOE Energy Innovation Hubs BES Funding Opportunities The Computational Materials and Chemical Sciences Network (CMCSN) Theoretical Condensed Matter Physics Scientific Highlights Reports and Activities Principal Investigators' Meetings BES Home Research Areas BES Funding Opportunities Print Text Size: A A A RSS Feeds FeedbackShare Page There are no funding opportunities specific to the Materials Sciences and Engineering Division at this time. Please visit the BES Funding Opportunities Page (link below) for general information on preparing applications to BES programs and for information on Funding Opportunities available to broader audiences than Materials

62

Staff to Share Networking Expertise and Accomplishments at Tech...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Are We Doing About It?" (1:30-3 p.m.) ESnet's Joe Metzger will describe "Building a Transatlantic Network"(4:15-5 p.m.) Wednesday, Oct. 29 ESnet's Bill Johnston will present...

63

Baryon Resonances Observed at BES  

E-Print Network [OSTI]

The $\\psi$ decays provide a novel way to explore baryon spectroscopy and baryon structure. The baryon resonances observed from $\\psi$ decays at BES are reviewed. The implications and prospects at upgraded BESIII/BEPCII are discussed.

B. S. Zou

2008-02-01T23:59:59.000Z

64

BES Reports | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

BES Reports Energy Frontier Research Centers (EFRCs) EFRCs Home Centers Research Grand Challenges BES Reports Science Highlights News & Events Publications History Contact BES Home...

65

Science-Driven Network Requirements for ESnet  

E-Print Network [OSTI]

Magnetic Fusion Energy Science.Magnetic Fusion Energy Science..data sets Magnetic Fusion Energy Science Executive Summary

2006-01-01T23:59:59.000Z

66

Science Highlights | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

Research Scientific Computing Center (NERSC) Argonne Leadership Computing Facility (ALCF) Oak Ridge Leadership Computing Facility (OLCF) Energy Sciences Network (ESnet) BES User...

67

BES and Congress | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

BES and Congress Basic Energy Sciences (BES) BES Home About Research Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee...

68

ESnet4_USA_Map_V2  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Science Network Requirements Report of the Fusion Energy Sciences Network Requirements Workshop Conducted March 13 and 14, 2008 FES Science Network Requirements Workshop Fusion...

69

NERSC/DOE BES Requirements Workshop Presentations  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Workshop Goals February 9, 2010 | Author(s): Yukiko Sekine | Workshop outline, logistics, format, procedures February 9, 2010 | Author(s): Richard Gerber | BES Program...

70

Recent Charmonium Results from BES  

E-Print Network [OSTI]

This paper summarizes recent results obtained from the BES psi(2S) data, which with 3.8 M events, is the world's largest data set. Distributions for psi(2S) -> pi^+ pi^- J/psi are fit to the Novikov-Shifman model. Preliminary branching fractions are reported for psi(2S) -> gamma f_2(1270) and gamma f_J(1710), as well as for decays into states containing an omega or phi. Finally recent measurements of the mass of the chi_c0 and eta_c are reported.

Frederick A. Harris; for the BES Collaboration

1999-10-14T23:59:59.000Z

71

Science-Driven Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Science-Driven Network Requirements for ESnet Update to the 2002 Office of Science Networking Requirements Workshop Report February 21, 2006 1-1 Science-Driven Network Requirements...

72

Collaborative Combustion Research with BES | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Combustion Research with BES Collaborative Combustion Research with BES 2012 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer...

73

BES_NERSC_Wang.ppt  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

A
DFT
nanostructure
calcula0on
 A
DFT
nanostructure
calcula0on
 case
study
 Lin-Wang
Wang
 Lawrence
Berkeley
Na0onal
Lab
 For BES/NERSC large scale simulation workshop A summary of mp304 NERSC account  Allocated and used computer time in 2009: ~ 1 M hours  Total number of users: ~ 7 active users  Main codes used: VASP, LAMMP, Petot, Escan, LS3DF  Number of topics (number of published papers): ~ 15  Number of processors for typical jobs: 16 to 1000, sometimes 10,000  Duration of the jobs: 20 minutes, to several hours, to a few days  The main considerations which determine the jobs we run: the physics problem, queue time and computer time.  Other facilities: no group cluster, INCITE project at NCCS and ALCF (but not discussed here).

74

ESnet 4 Helps Researchers Seeking the Origins of Matter | U.S...  

Office of Science (SC) Website

DOE Press Release... To Learn More: HPCwire Article... External link The US LHC Web Site... External link The CERN Web Site... External link ESnet Web Site... External...

75

Microsoft Word - ESnet Strategic Plan - March 2 2013.docx  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

! ! Strategic!Plan! FY20143FY2023! ESnet! ! March!1,!2013! ! ! ! ! ! ! ! ! This!work!was!supported!by!the!Director,!Office!of!Science,!Office!of!Advanced!! Scientific!Computing!Research!of!the!U.S.!Department!of!Energy!under!Contract!No.!DECAC02C05CH11231. ! ! Table&of&Contents& 1.&Facility&Overview&................................................................................................................&1! 2.&Mission,&Goals,&Drivers,&and&Strategic&Connections&.............................................................&4! 2.1!Vision!and!Mission!Statements!....................................................................................................................................!4! 2.2!Facility!Strategic!Goals!.....................................................................................................................................................!4!

76

Definition: Bes Emergency | Open Energy Information  

Open Energy Info (EERE)

Bes Emergency Bes Emergency Jump to: navigation, search Dictionary.png Bes Emergency failure of transmission facilities or generation supply that could adversely affect the reliability of the Bulk Electric System.[1] Also Known As BPS, Bulk Power System (Electricity transmission) Related Terms transmission lines, transmission line References ↑ Glossary of Terms Used in Reliability Standards An i LikeLike UnlikeLike You like this.Sign Up to see what your friends like. nline Glossary Definition Retrieved from "http://en.openei.org/w/index.php?title=Definition:Bes_Emergency&oldid=480539" Categories: Definitions ISGAN Definitions What links here Related changes Special pages Printable version Permanent link Browse properties 429 Throttled (bot load) Error 429 Throttled (bot load)

77

Sandia National Laboratories: BES Web Highlight: Single-mode...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ClimateECEnergyEnergy EfficiencyBES Web Highlight: Single-mode gallium nitride nanowire lasers BES Web Highlight: Single-mode gallium nitride nanowire lasers "Solid-state Lighting:...

78

Previous Workshops  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

About ESnet Overview ESnet Staff Governance Our Network Case Studies ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Network Requirements...

79

Exotica possibility of new observations by BES  

E-Print Network [OSTI]

The employment of interpolating currents of existed studies of four-quark state and glueball with QCD sum rule approach is analyzed. In terms of suitable currents, the masses of the lowest lying scalar and pseudo-scalar glueball were determined. The masses of some tetraquark states and their first orbital excitations were obtained through a combination of the sum rule with the constituent quark model. Exotica possibility of the new observations by BES is discussed.

Ailin Zhang

2007-12-21T23:59:59.000Z

80

Networking for the Future of Science ESnet Status Update  

E-Print Network [OSTI]

Allied Signal ARM KCP NOAA OSTI ORAU SRS JLAB PPPL Lab DC Offices MIT ANL BNL FNAL AMES NREL LLNL GA DOE

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to obtain the most current and comprehensive results.


81

Networking for the Future of Science ESnet Status Update  

E-Print Network [OSTI]

for that purpose. #12;YUCCA MT PNNL LANL SNLA Allied Signal ARM KCP NOAA OSTI ORAU SRS JLAB PPPL Lab DC Offices MIT

82

The Science DMZ Eli Dart, Network Engineer ESnet Engineering...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

1, 2011 Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science Overview Science Needs * Data tsunami, new science processes * Current problems *...

83

BioEnergy Solutions BES | Open Energy Information  

Open Energy Info (EERE)

California Zip: 93309 Product: Bakersfield-based firm installing and operating biogas plants for farmers and food producers. References: BioEnergy Solutions (BES)1 This...

84

NERSC/DOE BES Requirements Workshop Worksheet - Normand Modine  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Modine BES Requirements Worksheet 1.1. Project Information - Center for Integrated Nanotechnology (CINT) - Theory and Simulation Thrust Document Prepared By Normand Modine Project...

85

BES Budget | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

BES BES Budget Budget Budget Home About Budget by Program ASCR Budget BES Budget BER Budget FES Budget HEP Budget NP Budget WDTS Budget SLI & SS Budget SCPD Budget GAO Audit Reports External Links Contact Information Budget U.S. Department of Energy SC-41/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3541 F: (301) 903-9524 More Information » Budget by Program BES Budget Print Text Size: A A A RSS Feeds FeedbackShare Page The following links contain BES's budget request to Congress for current and prior years: FY2014 Budget Request to Congress .pdf file (1.1MB) FY2013 Budget Request to Congress .pdf file (844KB) FY2012 Budget Request to Congress .pdf file (662KB) FY2011 Budget Request to Congress .pdf file (466KB) FY2010 Budget Request to Congress .pdf file (551KB)

86

BER Science Network Requirements  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Network Requirements Report of the Biological and Environmental Research Network Requirements Workshop Conducted July 26 and 27, 2007 BER Science Network Requirements Workshop Biological and Environmental Research Program Office, DOE Office of Science Energy Sciences Network Bethesda, MD - July 26 and 27, 2007 ESnet is funded by the US Dept. of Energy, Office of Science, Advanced Scientific Computing Research (ASCR) program. Dan Hitchcock is the ESnet Program Manager. ESnet is operated by Lawrence Berkeley National Laboratory, which is operated by the University of California for the US Department of Energy under contract DE-AC02-05CH11231. This work was supported by the Directors of the Office of Science, Office of Advanced Scientific Computing Research, Facilities Division, and the Office of Biological &

87

Microsoft Word - ESnet JUNOS TiMOS Configurations for OSCARS Ethernet VLAN Circuit Services_ISIS-LDP-VPLS-v3.docx  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet ESnet J UNOS/TiMOS C onfigurations f or OSCARS E thernet V LAN C ircuit S ervices Using I S---IS, L DP, a nd l 2circuits Introduction This d ocument i s t o p rovide a b etter u nderstanding o f t he d ataplane c onfiguration that E Snet u ses t o p rovide O SCARS E thernet V LAN c ircuit s ervices o n J uniper a nd Alcatel r outers. T he e xample t opology (see F ig 1 .) i s m ade u p o f f our c onnected routers ( Juniper M 10, M X80, M X960, a nd A lcatel ( ALU) 7 750c4) with connections between t hem c onsisting o f 1 GE a nd 1 0GE l inks. Figure 1 . T opology S etup To c larify the configurations, three b i---directional c ircuits h ave b een c onfigured t o connect the three end---points ( netlab---pt4, n etlab---pt5, a nd n etlab---pt6) o ver d ifferent network p aths, a nd d ifferent V LAN I Ds f or t he s ervice h andoff.

88

Historic Sudbury Neutrino Observatory Data, Carried by ESnet, Lives on at  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Historic Sudbury Historic Sudbury Neutrino Observatory Data, Carried by ESnet, Lives on at NERSC Historic Sudbury Neutrino Observatory Data, Carried by ESnet, Lives on at NERSC January 26, 2010 | Tags: Astrophysics Contact: Linda Vu, lvu@lbl.gov, +1 510 486 2402 SNO.jpg SNO onsists of an 18-meters-in-diameter stainless steel geodesic sphere inside of which is an acrylic vessel filled with 1000 tons of heavy water (deuterium oxide or D2O). Attached to the sphere are 9,522 ultra-sensitive light-sensors called photomultiplier tubes. When neutrinos passing through the heavy water interact with deuterium nuclei, flashes of light are emitted. The photomultiplier tubes detect these light flashes and convert them into electronic signals that scientists can analyze for the presence

89

Basic Energy Sciences (BES) at LLNL  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

in GB Networks Coherency Does Not Equate to Stability Laser Crystallization of Phase Change Material Extraction of Equilibrium Energy and Kinetic Parameters from Single Molecule...

90

27264_ESNet_HEP_NP_Cover_final3_102113  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

HI data files over the WAN just as effectively as their HEP colleagues. It is a matter of upgrading the network capabilities into the Tier-3 sites in order to make this "diskless"...

91

BES Committees of Visitors | U.S. DOE Office of Science (SC)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Committees of Committees of Visitors Basic Energy Sciences (BES) BES Home About Staff Organization Chart .pdf file (51KB) BES Budget BES Committees of Visitors Directions Jobs Organizational History Research Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » About BES Committees of Visitors Print Text Size: A A A RSS Feeds FeedbackShare Page Office of Basic Energy Sciences (BES) Basic Energy Sciences Advisory Committee (BESAC) 2013 BESAC COV Report on Energy Frontier Research Centers and Joint

92

BES Committees of Visitors | U.S. DOE Office of Science (SC)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

BES BES Committees of Visitors Basic Energy Sciences Advisory Committee (BESAC) BESAC Home Meetings Members Charges/Reports Charter .pdf file (41KB) BES Committees of Visitors BES Home BES Committees of Visitors Print Text Size: A A A RSS Feeds FeedbackShare Page Office of Basic Energy Sciences (BES) Basic Energy Sciences Advisory Committee (BESAC) 2013 BESAC COV Report on Energy Frontier Research Centers and Joint Center for Artificial Photosynthesis Energy Innovation Hub (EFRC and JCAP) .pdf file (1.6MB) BES Response to BESAC COV Report on EFRC and JCAP .pdf file (30KB) BESAC COV Report on Division of Scientific User Facilities (SUF) .pdf file (398KB) BES Response to BESAC COV Report on SUF .pdf file (86KB) 2012 BESAC COV Report on Division of Materials Sciences and Engineering

93

26093_ESNet_Belle_II_Cover_v3  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Belle-II Experiment Network Requirements Belle-II Experiment Network Requirements Belle-II Experiment Collaboration Energy Sciences Network October 17-18, 2012 3 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or

94

NERSC-BES-Requirements-Yelick10.ppt  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Basic Energy Basic Energy Science Research Katherine Yelick NERSC Director Requirements Workshop NERSC Mission Accelerate the pace of scientific discovery for all DOE Office of Science (SC) research through computing and data systems and services. Efficient algorithms + flexible software + effective machines great computational science. 2 2010 Allocations NERSC is the Production Facility for DOE Office of Science * NERSC serves a large population Approximately 3000 users, 400 projects, 500 code instances * Focus on "unique" resources - Expert consulting and other services - High end computing systems - High end storage systems - Interface to high speed networking * Science-driven - Machine procured competitively using

95

BER Science Network Requirements  

SciTech Connect (OSTI)

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In April 2010 ESnet and the Office of Biological and Environmental Research, of the DOE Office of Science, organized a workshop to characterize the networking requirements of the science programs funded by BER. The requirements identified at the workshop are summarized and described in more detail in the case studies and the Findings section. A number of common themes emerged from the case studies and workshop discussions. One is that BER science, like many other disciplines, is becoming more and more distributed and collaborative in nature. Another common theme is that data set sizes are exploding. Climate Science in particular is on the verge of needing to manage exabytes of data, and Genomics is on the verge of a huge paradigm shift in the number of sites with sequencers and the amount of sequencer data being generated.

Dart, Eli; Tierney, Brian

2010-11-01T23:59:59.000Z

96

Third DOE BES Separations Research Workshop | U.S. DOE Office of Science  

Office of Science (SC) Website

Third DOE BES Separations Research Workshop Third DOE BES Separations Research Workshop Chemical Sciences, Geosciences, & Biosciences (CSGB) Division CSGB Home About Research Areas Scientific Highlights Reports & Activities Principal Investigators' Meetings BES Home Reports & Activities Third DOE BES Separations Research Workshop Print Text Size: A A A RSS Feeds FeedbackShare Page Third DOE/BES Separations Research Workshop Hilton DeSoto Hotel Savannah Georgia May 12-14, 1999 Organizing Committee Dr. Richard Gordon Richard.Gordon@science.doe.gov DOE/BES Separations & Analysis Prog. Dr. Charles H Byers cbyers@isopro.net Chem Tech Division Oak Ridge National Laboratory Dr. Hank Cochran hdc@ornl.gov Chem Tech Division Oak Ridge National Laboratory Prof. Robin Rogers robin@radar.ch.ua.edu Department of Chemistry

97

Archives of BES CRAs June 2008 | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

June 2008 June 2008 Basic Energy Sciences (BES) BES Home About Research Materials Sciences & Engineering (MSE) Chemical Sciences, Geosciences, and Biosciences (CSGB) Accelerator and Detector Research Research Conduct Policies DOE Energy Innovation Hubs Energy Frontier Research Centers National Nanotechnology Initiative (NNI) Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » Research Archives of BES CRAs June 2008 Print Text Size: A A A RSS Feeds FeedbackShare Page The research portfolio of the Basic Energy Sciences (BES) program consists

98

Archives of BES CRAs May 2006 | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

May 2006 May 2006 Basic Energy Sciences (BES) BES Home About Research Materials Sciences & Engineering (MSE) Chemical Sciences, Geosciences, and Biosciences (CSGB) Accelerator and Detector Research Research Conduct Policies DOE Energy Innovation Hubs Energy Frontier Research Centers National Nanotechnology Initiative (NNI) Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » Research Archives of BES CRAs May 2006 Print Text Size: A A A RSS Feeds FeedbackShare Page The research portfolio of the Basic Energy Sciences (BES) program consists

99

Archives of BES CRAs April 2003 | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

April 2003 April 2003 Basic Energy Sciences (BES) BES Home About Research Materials Sciences & Engineering (MSE) Chemical Sciences, Geosciences, and Biosciences (CSGB) Accelerator and Detector Research Research Conduct Policies DOE Energy Innovation Hubs Energy Frontier Research Centers National Nanotechnology Initiative (NNI) Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » Research Archives of BES CRAs April 2003 Print Text Size: A A A RSS Feeds FeedbackShare Page The research portfolio of the Basic Energy Sciences (BES) program consists

100

Basic Energy Sciences (BES) Homepage | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

BES Home BES Home Basic Energy Sciences (BES) BES Home About Research Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » Science for Energy Discovery science solves mysteries, sparks innovation, and stimulates future technologies. This principle provides the inspiration for the fundamental energy research and the remarkable collection of major scientific user facilities supported by Basic Energy Sciences.Read More Discovery Science Materials Sciences and Engineering Understanding, predicting, and controlling materials and their

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Biological and Environmental Research Network Requirements  

SciTech Connect (OSTI)

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet be a highly successful enabler of scientific discovery for over 25 years. In November 2012, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the BER program office. Several key findings resulted from the review. Among them: 1) The scale of data sets available to science collaborations continues to increase exponentially. This has broad impact, both on the network and on the computational and storage systems connected to the network. 2) Many science collaborations require assistance to cope with the systems and network engineering challenges inherent in managing the rapid growth in data scale. 3) Several science domains operate distributed facilities that rely on high-performance networking for success. Key examples illustrated in this report include the Earth System Grid Federation (ESGF) and the Systems Biology Knowledgebase (KBase). This report expands on these points, and addresses others as well. The report contains a findings section as well as the text of the case studies discussed at the review.

Dart, Eli; Tierney, Brian

2013-09-01T23:59:59.000Z

102

Report on Hydrogen Storage Panel Findings in DOE-BES Sponsored...  

Broader source: Energy.gov (indexed) [DOE]

Report on Hydrogen Storage Panel Findings in DOE-BES Sponsored Workshop on Basic Research for Hydrogen Production, Storage and Use Report on Hydrogen Storage Panel Findings in...

103

Recent Charmonium Results from BES (Talk Presented at DPF99)  

E-Print Network [OSTI]

Recent results obtained from the BES psi(2S) data are summarized, including the measurement of the branching ratio of the J/psi to leptons, B(J/psi -> l^+ l^-) = 5.87 +/- 0.04 +/- 0.09, many psi(2S) and chi_c branching ratios, information on the rho-pi puzzle, and measurements of the mass of the chi_c0, m(chi_c0) = 3414.1 +/- 0.6 +/- 0.8 MeV, and the eta_c, m(eta_c) = 2975.8 +/- 3.9 +/- 1.2 MeV.

F. A. Harris

1999-03-17T23:59:59.000Z

104

Benefits of Green Energy and Proportionality in High Speed Wide Area Networks Connecting Data Centers  

E-Print Network [OSTI]

Benefits of Green Energy and Proportionality in High Speed Wide Area Networks Connecting Data Network ModelBackbone Network Model Green EnergyGreen Energy SPR vs. GEARSPR vs. GEAR All vs. Necessary (MuSyC), National Science Foundation (NSF) Project GreenLight, Energy Sciences Network (ESnet), NSF

Simunic, Tajana

105

Archives of BES CRAs February 2002 | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

February 2002 February 2002 Basic Energy Sciences (BES) BES Home About Research Materials Sciences & Engineering (MSE) Chemical Sciences, Geosciences, and Biosciences (CSGB) Accelerator and Detector Research Research Conduct Policies DOE Energy Innovation Hubs Energy Frontier Research Centers National Nanotechnology Initiative (NNI) Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » Research Archives of BES CRAs February 2002 Print Text Size: A A A RSS Feeds FeedbackShare Page

106

Archives of BES CRAs October 2004 | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

October 2004 October 2004 Basic Energy Sciences (BES) BES Home About Research Materials Sciences & Engineering (MSE) Chemical Sciences, Geosciences, and Biosciences (CSGB) Accelerator and Detector Research Research Conduct Policies DOE Energy Innovation Hubs Energy Frontier Research Centers National Nanotechnology Initiative (NNI) Facilities Science Highlights Benefits of BES Funding Opportunities Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » Research Archives of BES CRAs October 2004 Print Text Size: A A A RSS Feeds FeedbackShare Page

107

DOE-BES Chemical Sciences Highlights of Progress in Separations Sciences  

Office of Science (SC) Website

DOE-BES Chemical Sciences Highlights of Progress in DOE-BES Chemical Sciences Highlights of Progress in Separations Sciences 1980-1999 Chemical Sciences, Geosciences, & Biosciences (CSGB) Division CSGB Home About Research Areas Scientific Highlights Reports & Activities Principal Investigators' Meetings BES Home Reports & Activities DOE-BES Chemical Sciences Highlights of Progress in Separations Sciences 1980-1999 Print Text Size: A A A RSS Feeds FeedbackShare Page DOE-BES Chemical Sciences Highlights of Progress in Separations Sciences 1980-1999 Edited by Charles H. Byers IsoPro International Inc. 2140 Santa Cruz Ave, #C304 Menlo Park, CA 94025 DOE Chemical Sciences Highlights of Progress in Separations Sciences Introduction The singular wartime success of the Manhattan project was, in large part, due to the fact that project chemists, led by Glenn Seaborg, leveraged

108

NERSC/DOE BES Requirements Workshop Worksheet - Peter Cummings  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Peter Cummings Peter Cummings Peter Cummings BES Requirements Worksheet 1.1. Project Information - Molecular-Based Simulation of Complex and Nanostructured Fluids Document Prepared By Peter Cummings Project Title Molecular-Based Simulation of Complex and Nanostructured Fluids Principal Investigator Peter Cummings Participating Organizations Vanderbilt University Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: DOE/EERE 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a brief description of your project - highlighting its computational aspect - and outline its scientific objectives for the next 3-5 years. Please list one or two specific goals you hope to reach in 5 years. We perform primarily molecular dynamics simulations of nanostructured

109

NERSC/DOE BES Requirements Workshop Worksheet - Mark Jarrell  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Mark Jarrell Mark Jarrell Mark Jarrell BES Requirements Worksheet 1.1. Project Information - SciDAC: Next Generation Multi-Scale Quantum Simulation Software for Strongly Correlated Materials Document Prepared By Mark Jarrell Project Title SciDAC: Next Generation Multi-Scale Quantum Simulation Software for Strongly Correlated Materials Principal Investigator Mark Jarrell Participating Organizations Louisiana State University Ohio SuperComputer Center UC Davis ORNL Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a brief description of your project - highlighting its computational aspect - and outline its scientific objectives for the next 3-5 years. Please list one or two specific goals you hope to reach in 5

110

NERSC/DOE BES Requirements Workshop Worksheet - Jeffrey B. Neaton  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Jeffrey B. Neaton Jeffrey B. Neaton Jeffrey B. Neaton BES Requirements Worksheet 1.1. Project Information - Charge Transport and Excited States at Interfaces in Nanostructured Materials Document Prepared By Jeffrey B. Neaton Project Title Charge Transport and Excited States at Interfaces in Nanostructured Materials Principal Investigator Jeffrey B. Neaton Participating Organizations Lawrence Berkeley National Laboratory Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a brief description of your project - highlighting its computational aspect - and outline its scientific objectives for the next 3-5 years. Please list one or two specific goals you hope to reach in 5 years. Over the next 3-5 years, we seek to develop and apply first-principles

111

IPv6 Implementation Checklist  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

IPv6 Implementation Checklist Engineering Services The Network OSCARS Fasterdata IPv6 Network IPv6 Implementation Checklist ESnet IPv6 Mirror Servers ESnet IPv6 History ESnet...

112

Kelly Gonzalez  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Kelly Gonzalez About ESnet Our Mission The Network ESnet History Governance & Policies Career Opportunities ESnet Staff & Org Chart Administration Advanced Network Technologies...

113

Brendan M. White  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Brendan M. White About ESnet Our Mission The Network ESnet History Governance & Policies Career Opportunities ESnet Staff & Org Chart Administration Advanced Network Technologies...

114

Daniel White  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Daniel White About ESnet Our Mission The Network ESnet History Governance & Policies Career Opportunities ESnet Staff & Org Chart Administration Advanced Network Technologies...

115

Microsoft PowerPoint - 2010 CEDS Peer Review SEI OCTAVE BES.pptx  

Broader source: Energy.gov (indexed) [DOE]

CERT OCTAVE BES CERT OCTAVE BES Summary Slide: CERT OCTAVE BES Guidance in Identifying and Managing Electricity Sector Risk Outcomes: An operational cyber security risk assessment approach for the BES community. Roadmap Challenges: Limited ability to measure and assess cyber security posture, lack of consistent security posture, lack of consistent cyber security metrics, poor understanding of cyber risks, and weak business case for cyber security investments. Major Successes: Assessment methodology codified and first pilot scheduled to begin in August. Schedule: Pilot (08/10), Draft Methodology Report (09/10), Pilots 2 and 3 (10/10), Final Report and Training available (12/10). Level of Effort: $300K Funds Remaining: $234K Performers: SEI Partners: NERC CIP, AECC, and

116

A Systematic Methodology to Underpin the CC Process Using Calibrated BES Models  

E-Print Network [OSTI]

supplies all heating systems in the building. Stand-alone direct exchange units cool the computer rooms. Using the whole building energy simulation package EnergyPlus it was possible to simulate these HVAC systems. Complexities in drafting the BES... (ppm); ? Electrical Energy Consumption (kWh); ? Heat Energy Consumption (kWh). Initial investigations revealed that data was being discarded every 10 days. The EMCS was modified to record all values to allow for the calibration of an annual BES...

White, G.; Keane, M.; Raftery, P.; Coakley, D.

2011-01-01T23:59:59.000Z

117

STAGES -ENSEIGNEMENT AU SECONDAIRE (BES) ANGLAIS LANGUE SECONDE (BEALS) Programme Dure / Rythme Calendrier Milieux de  

E-Print Network [OSTI]

STAGES - ENSEIGNEMENT AU SECONDAIRE (BES) ANGLAIS LANGUE SECONDE (BEALS) Programme Durée / Rythme'enseignante ou l'enseignant associé BES/BEALS STP 100 (2 cr) STP 111 (2 cr) Niveau 1 Valeur 1 10 jours 10 jours perlés (dont 1 journée au primaire pour le BEALS) Les mercredis 17 sept., 1er , 8, 22, 29 oct., 5, 19, 26

Spino, Claude

118

Michael Pfannenstiel  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies ESnet Strategic Plan ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering...

119

Michael Bennett  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies ESnet Strategic Plan ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering...

120

Mark Redman  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies ESnet Strategic Plan ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering...

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Mary Thompson  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies ESnet Strategic Plan ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering...

122

Sheila Cisko  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies ESnet Strategic Plan ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering...

123

Daniel Peterson  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies ESnet Strategic Plan ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering...

124

Patty Giuntoli  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies ESnet Strategic Plan ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering...

125

David Foster  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

David Foster About ESnet Our Mission The Network ESnet History Governance & Policies ESnet Policy Board Larry Smarr Jagdeep Singh Kristin Rauschenbach Cees de Laat David Foster...

126

Facility Data Policy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Facility Data Policy About ESnet Our Mission The Network ESnet History Governance & Policies ESnet Policy Board ESCC Acceptable Use Policy Facility Data Policy Career Opportunities...

127

BES Committees of Visitors | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

BES Committees of Visitors BES Committees of Visitors Deputy Director for Science Programs Deputy Director Home Mission & Functions Deputy Director Biography Organization Staff Presentations & Testimony Federal Advisory Committees Committees of Visitors ASCR Committees of Visitors BES Committees of Visitors BER Committees of Visitors FES Committees of Visitors HEP Committees of Visitors NP Committees of Visitors WDTS Committees of Visitors Contact Information Deputy Director for Science Programs U.S. Department of Energy SC-2/Forrestal Building 1000 Independence Ave., SW Washington, DC 20585 P: (202) 586-5430 F: (202) 586-4120 E: sc.science@science.doe.gov U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-5316 F: (301) 903-7780 E: sc.science@science.doe.gov

128

Sigma, Kappa and fo(980) in E791 and BES II data  

E-Print Network [OSTI]

Both sigma and kappa are well established from E791 data on D->3pi and D->K-pi-pi$ and BES II data on J/Psi->omega-pi-pi and KKpipi. Fits to these data are accurately consistent with pi-pi and Kpi elastic scattering when one allows for the Adler zero which arises from Chiral Symmetry Breaking. The phase variation with mass is also consistent between elastic scattering and production data.

D. V. Bugg

2005-10-06T23:59:59.000Z

129

BER Science Network Requirements Workshop -- July 26-27,2007  

SciTech Connect (OSTI)

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States of America. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In July 2007, ESnet and the Biological and Environmental Research (BER) Program Office of the DOE Office of Science organized a workshop to characterize the networking requirements of the science programs funded by the BER Program Office. These included several large programs and facilities, including Atmospheric Radiation Measurement (ARM) Program and the ARM Climate Research Facility (ACRF), Bioinformatics and Life Sciences Programs, Climate Sciences Programs, the Environmental Molecular Sciences Laboratory at PNNL, the Joint Genome Institute (JGI). National Center for Atmospheric Research (NCAR) also participated in the workshop and contributed a section to this report due to the fact that a large distributed data repository for climate data will be established at NERSC, ORNL and NCAR, and this will have an effect on ESnet. Workshop participants were asked to codify their requirements in a 'case study' format, which summarizes the instruments and facilities necessary for the science and the process by which the science is done, with emphasis on the network services needed and the way in which the network is used. Participants were asked to consider three time scales in their case studies--the near term (immediately and up to 12 months in the future), the medium term (3-5 years in the future), and the long term (greater than 5 years in the future). In addition to achieving its goal of collecting and characterizing the network requirements of the science endeavors funded by the BER Program Office, the workshop emphasized some additional points. These included the need for a future ESnet presence in the Denver area, a desire for ESnet to continue support of collaboration services, and the need for ESnet to support dedicated bandwidth or 'virtual circuit' services. In addition, it is clear that the BER facilities are going to experience significant growth in data production over the next 5 years. The reasons for this vary (model resolution and supercomputer allocations for climate, detector upgrades for EMSL and ARM, sequencing hardware upgrades for JGI), but all indicators point to significant growth in data volumes over the near to medium term. This growth in data volume, combined with the ever-expanding scope of scientific collaboration, will continue to demand ever-increasing bandwidth, reliability and service richness from the networks that support DOE science.

Tierney, Brian L.; Dart, Eli

2008-02-01T23:59:59.000Z

130

A New Approach in Advance Network Reservation and Provisioning for High-Performance Scientific Data Transfers  

SciTech Connect (OSTI)

Scientific applications already generate many terabytes and even petabytes of data from supercomputer runs and large-scale experiments. The need for transferring data chunks of ever-increasing sizes through the network shows no sign of abating. Hence, we need high-bandwidth high speed networks such as ESnet (Energy Sciences Network). Network reservation systems, i.e. ESnet's OSCARS (On-demand Secure Circuits and Advance Reservation System) establish guaranteed bandwidth of secure virtual circuits at a certain time, for a certain bandwidth and length of time. OSCARS checks network availability and capacity for the specified period of time, and allocates requested bandwidth for that user if it is available. If the requested reservation cannot be granted, no further suggestion is returned back to the user. Further, there is no possibility from the users view-point to make an optimal choice. We report a new algorithm, where the user specifies the total volume that needs to be transferred, a maximum bandwidth that he/she can use, and a desired time period within which the transfer should be done. The algorithm can find alternate allocation possibilities, including earliest time for completion, or shortest transfer duration - leaving the choice to the user. We present a novel approach for path finding in time-dependent networks, and a new polynomial algorithm to find possible reservation options according to given constraints. We have implemented our algorithm for testing and incorporation into a future version of ESnet?s OSCARS. Our approach provides a basis for provisioning end-to-end high performance data transfers over storage and network resources.

Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex

2010-01-28T23:59:59.000Z

131

Photon Speedway Puts Big Data In the Fast Lane  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

from Berkeley Lab and SLAC are using NERSC and ESnet to achieve breakthroughs in photosynthesis research August 26, 2014 | Tags: Basic Energy Sciences (BES), Data Transfer,...

132

Joseph Metzger  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Joseph Metzger Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

133

Michael O'Connor  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

O'Connor Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

134

Patrick Dorn  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Patrick Dorn Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

135

Nick Buraglio  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Nick Buraglio Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

136

David Mitchell  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

David Mitchell Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

137

Chin Guok  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Chin Guok Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

138

Patty Giuntoli  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Patty Giuntoli Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

139

Services  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Services Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

140

Yvonne Hines  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Yvonne Hines Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet...

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Michael Sinatra  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Sinatra Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet (Inside...

142

ESnet Update Summer 2007  

E-Print Network [OSTI]

;2 TWC SNLL YUCCA MT PNNL LIGO INEEL LANL SNLA Allied Signal ARM KCP NOAA OSTI ORAU SRS JLAB PPPL Lab DC

143

ESnet4_cover  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

remains the premier instrument for measuring BAO. A collaboration led by LBNL is upgrading the SDSS spectrographs and pursuing a dedicated BAO experiment from 2009 through...

144

Who ESnet Serves  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Ames Laboratory (Ames, IA) ANL Argonne National Laboratory (Argonne, IL) BECHTEL-NV NSTec National Securities Technology (North Las Vegas, NV) BJC Bechtel Jacobs Corporation...

145

The Computational Materials and Chemical Sciences Network (CMCSN) | U.S.  

Office of Science (SC) Website

The Computational Materials and Chemical Sciences Network (CMCSN) The Computational Materials and Chemical Sciences Network (CMCSN) Materials Sciences and Engineering (MSE) Division MSE Home About Research Areas Energy Frontier Research Centers (EFRCs) DOE Energy Innovation Hubs BES Funding Opportunities The Computational Materials and Chemical Sciences Network (CMCSN) Theoretical Condensed Matter Physics Scientific Highlights Reports and Activities Principal Investigators' Meetings BES Home Research Areas The Computational Materials and Chemical Sciences Network (CMCSN) Print Text Size: A A A RSS Feeds FeedbackShare Page The U.S. Department of Energy, Office of Basic Energy Sciences, provides support for Computational Materials and Chemical Sciences Network (CMCSN) projects through the Theoretical Condensed Matter Physics & Theoretical

146

Validation of Simulated Thermal Comfort using a Calibrated Building Energy Simulation (BES) model in the context of Building Performance Evaluation & Optimisation  

E-Print Network [OSTI]

Building Energy Simulation (BES) models play a significant role in the design and optimisation of buildings. Simulation models may be used to compare the cost-effectiveness of Energy- Conservation Measures (ECMs) in the design stage as well...

Coakley, D.; Corry, E. J.; Keane, M. M.

2013-01-01T23:59:59.000Z

147

Energy-Efficient Networks  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Architecting and Operating Architecting and Operating Energy-Efficient Networks Inder Monga (ESnet) With input from Dan Kilper, Thierry Klein (Bell Labs) Vijay Sivaraman (UNSW, Australia) Jaafar Elmirghani (University of Leeds, UK) § Global research consortium representing industry, government and academic organizations § Launched in May 2010 § Focus on sustainability and growth § Holistic and ambitious: Goal of 1000x § 57 member organizations § 300+ leading scientists § Recognized by the World Economic Forum as an industry-led best practice toward sustainability DELIVER ARCHITECTURE, SPECIFICATIONS AND SOLUTIONS AND DEMONSTRATE KEY TECHNOLOGIES TO INCREASE NETWORK ENERGY EFFICIENCY BY A FACTOR 1000 COMPARED TO 2010 GREENTOUCH(tm) (www.greentouch.org)

148

Using Graphite to view network data  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Graphite Graphite to Visualize Network Data Jon Dugan Summer ESCC 2010, Columbus, OH Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science ESnet Statistics Overview ESxSNMP (Data Collection) ESxSNMP (Data Collection) Graphite (Visualization) Graphite (Visualization) Analytics (Custom Reports) Analytics (Custom Reports) Net Almanac (Metadata) Net Almanac (Metadata) Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science What is Graphite? "Enterprise scalable realtime graphing" * Developed by Orbitz for visualizing internal performance data * Open source: https://launchpad.net/graphite * Has own RRD like database called Carbon * RRD Compatible ESxSNMP Integration * via REST interface * Easy integration, Graphite is well written

149

Peering Connections  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services The Network Peering Connections Engineering Services The...

150

OSCARS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services OSCARS Engineering Services The Network OSCARS How It Works Who's...

151

Who's Using OSCARS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services OSCARS Who's Using OSCARS? Engineering Services The Network...

152

Read More...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services OSCARS Read More... Engineering Services The Network OSCARS How...

153

Science DMZ at the University of Florida  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet Overview ESnet Staff Governance Our Network Case Studies OSCARS Case Studies Science DMZ Case Studies Science DMZ UF Science DMZ CU Science DMZ Penn State & VTTI Science...

154

Microsoft Word - The_Advanced_Networks_and_Services_Underpinning_Modern,Large-Scale_Science.SciDAC.v5.doc  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

: Advanced Networking and Services : Advanced Networking and Services Supporting the Science Mission of DOE's Office of Science William E. Johnston ESnet Dept. Head and Senior Scientist Lawrence Berkeley National Laboratory May, 2007 1 Introduction In many ways, the dramatic achievements in scientific discovery through advanced computing and the discoveries of the increasingly large-scale instruments with their enormous data handling and remote collaboration requirements, have been made possible by accompanying accomplishments in high performance networking. As increasingly advanced supercomputers and experimental research facilities have provided researchers powerful tools with unprecedented capabilities, advancements in networks connecting scientists to these tools have made these research facilities available to broader communities

155

High Energy Physics and Nuclear Physics Network Requirements  

SciTech Connect (OSTI)

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements needed by instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In August 2013, ESnet and the DOE SC Offices of High Energy Physics (HEP) and Nuclear Physics (NP) organized a review to characterize the networking requirements of the programs funded by the HEP and NP program offices. Several key findings resulted from the review. Among them: 1. The Large Hadron Collider?s ATLAS (A Toroidal LHC Apparatus) and CMS (Compact Muon Solenoid) experiments are adopting remote input/output (I/O) as a core component of their data analysis infrastructure. This will significantly increase their demands on the network from both a reliability perspective and a performance perspective. 2. The Large Hadron Collider (LHC) experiments (particularly ATLAS and CMS) are working to integrate network awareness into the workflow systems that manage the large number of daily analysis jobs (1 million analysis jobs per day for ATLAS), which are an integral part of the experiments. Collaboration with networking organizations such as ESnet, and the consumption of performance data (e.g., from perfSONAR [PERformance Service Oriented Network monitoring Architecture]) are critical to the success of these efforts. 3. The international aspects of HEP and NP collaborations continue to expand. This includes the LHC experiments, the Relativistic Heavy Ion Collider (RHIC) experiments, the Belle II Collaboration, the Large Synoptic Survey Telescope (LSST), and others. The international nature of these collaborations makes them heavily reliant on transoceanic connectivity, which is subject to longer term service disruptions than terrestrial connectivity. The network engineering aspects of undersea connectivity will continue to be a significant part of the planning, deployment, and operation of the data analysis infrastructure for HEP and NP experiments for the foreseeable future. Given their critical dependency on networking services, the experiments have expressed the need for tight integration (both technically and operationally) of the domestic and the transoceanic parts of the network infrastructure that supports the experiments. 4. The datasets associated with simulations continue to increase in size, and the need to move these datasets between analysis centers is placing ever-increasing demands on networks and on data management systems at the supercomputing centers. In addition, there is a need to harmonize cybersecurity practice with the data transfer performance requirements of the science. This report expands on these points, and addresses others as well. The report contains a findings section in addition to the text of the case studies discussed during the review.

Dart, Eli; Bauerdick, Lothar; Bell, Greg; Ciuffo, Leandro; Dasu, Sridhara; Dattoria, Vince; De, Kaushik; Ernst, Michael; Finkelson, Dale; Gottleib, Steven; Gutsche, Oliver; Habib, Salman; Hoeche, Stefan; Hughes-Jones, Richard; Ibarra, Julio; Johnston, William; Kisner, Theodore; Kowalski, Andy; Lauret, Jerome; Luitz, Steffen; Mackenzie, Paul; Maguire, Chales; Metzger, Joe; Monga, Inder; Ng, Cho-Kuen; Nielsen, Jason; Price, Larry; Porter, Jeff; Purschke, Martin; Rai, Gulshan; Roser, Rob; Schram, Malachi; Tull, Craig; Watson, Chip; Zurawski, Jason

2014-03-02T23:59:59.000Z

156

Advanced Scientific Computing Research User Facilities | U.S. DOE Office of  

Office of Science (SC) Website

ASCR User Facilities ASCR User Facilities User Facilities ASCR User Facilities BES User Facilities BER User Facilities FES User Facilities HEP User Facilities NP User Facilities User Facilities Frequently Asked Questions User Facility Science Highlights Contact Information Office of Science U.S. Department of Energy 1000 Independence Ave., SW Washington, DC 20585 P: (202) 586-5430 ASCR User Facilities Print Text Size: A A A RSS Feeds FeedbackShare Page The Advanced Scientific Computing Research program supports the operation of the following national scientific user facilities: Energy Sciences Network (ESnet): External link The Energy Sciences Network, or ESnet External link , is the Department of Energy's high-speed network that provides the high-bandwidth, reliable connections that link scientists at national laboratories, universities and

157

Phoebus: Network Middleware for Next-Generation Network Computing  

SciTech Connect (OSTI)

The Phoebus project investigated algorithms, protocols, and middleware infrastructure to improve end-to-end performance in high speed, dynamic networks. The Phoebus system essentially serves as an adaptation point for networks with disparate capabilities or provisioning. This adaptation can take a variety of forms including acting as a provisioning agent across multiple signaling domains, providing transport protocol adaptation points, and mapping between distributed resource reservation paradigms and the optical network control plane. We have successfully developed the system and demonstrated benefits. The Phoebus system was deployed in Internet2 and in ESnet, as well as in GEANT2, RNP in Brazil and over international links to Korea and Japan. Phoebus is a system that implements a new protocol and associated forwarding infrastructure for improving throughput in high-speed dynamic networks. It was developed to serve the needs of large DOE applications on high-performance networks. The idea underlying the Phoebus model is to embed Phoebus Gateways (PGs) in the network as on-ramps to dynamic circuit networks. The gateways act as protocol translators that allow legacy applications to use dedicated paths with high performance.

Martin Swany

2012-06-16T23:59:59.000Z

158

Visio-ESnetBackbone.vsd  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

by Mark Redman by Mark Redman Revised: Revised by John Paul Jones This Map is for DOE Business Use Only. Do Not Redistribute. For copies contact info@es.net US R&E International R&E Peering Commercial Commercial Peering International Peering OC12-Link(622Mb) NLR 10 GE Circuit Internet 2 10GE-SDN-Circuit Internet2 10GE-IP-Circuit 1GE-Link S D N 10GE-Link IP MAN SITE MAN 10 GE RING SITE OC48-Link(2.48Gb) OC3-Link(155Mb) FE-Link(100Mb) DS3-Link(45Mb) T1-Link(1.45Mb) Ether-Link(10Mb) R&E and International 10G Peering Connections R&E and International 1G Peering Connections PerfSonar enabled perfSONAR 8/3/2010 CANADA (CANARIE) CENIC/DREN/ INTERNET2/ LOS NETTOS/ NASA/NLR ASIA-PACIFIC (KAREN/KREONET2/NUS-GP/ ODN/REANNZ/SINET/TANET2/ TRANSPAC2) AUSTRALIA (AARnet) CENIC/INTERNET2/ LOS NETTOS/NASA ASIA-PACIFIC

159

Advanced Scientific Computing Research Network Requirements  

E-Print Network [OSTI]

Plasma Physics Laboratory (PPPL). ESnet and ORNL willOSF PB/sec Pbps perfSONAR PF PPPL PTF PVFS QDR RDMA REST RPI

Dart, Eli

2014-01-01T23:59:59.000Z

160

Biological and Environmental Research Network Requirements  

E-Print Network [OSTI]

Cesar Izaurralde, PNNL (GLBRC) Bill Johnston, ESnet (Bioenergy Research Center (GLBRC) needs assistance with dataBioenergy Research Center (GLBRC) has developed a high-

Dart, Eli

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

DOE Launches First Segment of its Next-Generation Nationwide Network to  

Broader source: Energy.gov (indexed) [DOE]

First Segment of its Next-Generation Nationwide First Segment of its Next-Generation Nationwide Network to Support Scientific Research Efforts DOE Launches First Segment of its Next-Generation Nationwide Network to Support Scientific Research Efforts May 30, 2007 - 1:24pm Addthis WASHINGTON, DC- The U.S. Department of Energy's (DOE) Office of Science and Internet2 announced today that the first segment of a next-generation, nationwide network has gone live, marking a key step in significantly upgrading networking services to thousands of scientific researchers across the country and around the world. The first complete national ring of DOE's Energy Sciences Network (ESnet4) will be rolled out segment by segment from the east coast to the west coast and is expected to be fully operational by September, 2007.

162

ESCC Evening Discussion: High Performance Data Transfer Eli Dart, Network Engineer  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESCC Evening Discussion: ESCC Evening Discussion: High Performance Data Transfer Eli Dart, Network Engineer ESnet Network Engineering Group Summer ESCC/Joint Techs Columbus, OH July 14, 2010 Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science High Performance Data Transfer * This is a broad topic with several components * Last discussion - perfSONAR * Tonight's discussion - possible next steps to increase the performance achieved by scientists in their use of the network - What is "the network" from a user's perspective? - Deployment of dedicated systems - Need for cooperation - Do the easy stuff first 7/13/10 2 Lawrence Berkeley National Laboratory U.S. Department of Energy | Office of Science Data Transfer Is A Tractable Problem

163

Large Scale Computing Requirements for Basic Energy Sciences (An BES / ASCR / NERSC Workshop) Hilton Washington DC/Rockville Meeting Center, Rockville MD 3D Geophysical Imaging  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Requirements Requirements for Basic Energy Sciences (An BES / ASCR / NERSC Workshop) Hilton Washington DC/Rockville Meeting Center, Rockville MD 3D Geophysical Modeling and Imaging G. A. Newman Lawrence Berkeley National Laboratory February 9 - 10 , 2010 Talk Outline * SEAM Geophysical Modeling Project - Its Really Big! * Geophysical Imaging (Seismic & EM) - Its 10 to 100x Bigger! - Reverse Time Migration - Full Waveform Inversion - 3D Imaging & Large Scale Considerations - Offshore Brazil Imaging Example (EM Data Set) * Computational Bottlenecks * Computing Alternatives - GPU's & FPGA's - Issues Why ? So that the resource industry can tackle grand geophysical challenges (Subsalt imaging, land acquisition, 4-D, CO2, carbonates ......) SEAM Mission Advance the science and technology of applied

164

BES Energy Storage Research  

Broader source: Energy.gov [DOE]

2013 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting

165

Recent BES charmonium results  

E-Print Network [OSTI]

Using 58 million $J/\\psi$ decays, we have investigated the $p \\bar{p}$ invariant mass spectrum in the radiative decay $J/\\psi \\to \\gamma p \\bar{p}$ and observe a prominent structure with mass near $2m_p$. Fitting with an S-wave Breit-Wigner, we obtain a peak mass of $M= 1859^{+3}_{-10}(\\rm stat)^{+5}_{-25}(sys) MeV/c^2$. $J/\\psi \\to \\gamma \\eta_c$ decays from the same sample are used to determine the mass, width, and hadronic branching ratios of the $\\eta_c$. From a sample of 14 million $\\psi(2S)$ events, the first observation of $\\chi_{cJ}$ (J=0,1,2) decays to $\\Lambda\\bar{\\Lambda}$ is made, and branching ratios are determined, which are larger than expected from the Color Octet Model. Branching ratios of $K_s^0K_L^0$ in both $\\psi(2S)$ and $J/\\psi$ decays are measured, and a more than four sigma deviation from the pQCD predicted "12% rule" is observed. In $\\psi(3770)$ decays, evidence for the non-$D\\bar{D}$ decay to $\\pi^+\\pi^-J/\\psi$ is observed.

Jiangchuan Chen; Frederick A. Harris

2003-10-16T23:59:59.000Z

166

BES Open Funding Opportunities  

Office of Science (SC) Website

- and is the principal federal funding agency of - the Nation's research programs in high-energy physics, nuclear physics, and fusion energy sciences. en CD8F561D-CA7E-4C24-B0AD-2...

167

NERSC-BES.pptx  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

e stablished a t N ERSC 1994 Cray T 3D M PP t estbed 1994 --- 2000 TransiOoned u sers f rom v ector processing t o M PP 1996 Moved t o B erkeley L ab 1996 PDSF d ata i ntensive c...

168

BES Science Highlights  

Office of Science (SC) Website

phase separation. The teams research was featured on the January 2014 cover of Green Chemistry.

5B7F66D7-7B75-432D-87FA-EBFD9652FB85http:science.energy.gov...

169

Microsoft Word - The Essential Role of New Network Services for High Performance Distributed Computing - PARENG.CivilComp.2011.  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

International Conference on Parallel, Distributed, Grid and International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering 12-15 April 2011, Ajaccio - Corsica - France In "Trends in Parallel, Distributed, Grid and Cloud Computing for Engineering," Edited by: P. Iványi, B.H.V. Topping, Civil-Comp Press. Network Services for High Performance Distributed Computing and Data Management W. E. Johnston, C. Guok, J. Metzger, and B. Tierney ESnet and Lawrence Berkeley National Laboratory, Berkeley California, U.S.A Keywords: high performance distributed computing and data management, high throughput networks, network services, science use of networks Much of modern science is dependent on high performance distributed computing and data handling. This distributed infrastructure, in turn, depends on

170

Fasterdata  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Services Fasterdata Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1...

171

Evangelos Chaniotakis  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Evangelos Chaniotakis Engineering Services The Network OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1...

172

OSCARS Developer Community  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Web Browser Interface (WBUI) Web Service Interface (API) Read More... Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Network R&D Overview...

173

Eli Dart  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Eli Dart Eli Dart About ESnet Overview ESnet Staff Administration Advanced Network Technologies Audio, Video, Data Collaboration (ECS) Infrastructure and Identity Network Engineering Office of the CTO Operations and Deployment Science Engagement Tools Team Governance Our Network Case Studies ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Eli Dart dart.png Eli Dart Network Engineer Network Engineering Services Group Dart@es.net Eli Dart is responsible for configuration and troubleshooting the ESnet's infrastructure, solving performance problems, and planning for future

174

Microsoft Word - Johnston.IOS.Network Communication as a Service-Oriented Capability.5.doc  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Communication as a Service-Oriented Communication as a Service-Oriented Capability William JOHNSTON, Joe METZGER, Mike O'CONNOR, Michael COLLINS, Joseph BURRESCIA, Eli DART, Jim GAGLIARDI, Chin GUOK, and Kevin OBERMAN ESnet, Lawrence Berkeley National Laboratory Abstract. In widely distributed systems generally, and in science-oriented Grids in particular, software, CPU time, storage, etc., are treated as "services" - they can be allocated and used with service guarantees that allows them to be integrated into systems that perform complex tasks. Network communication is currently not a service - it is provided, in general, as a "best effort" capability with no guarantees and only statistical predictability. In order for Grids (and most types of systems with widely

175

Reports  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Reports Reports About ESnet Overview ESnet Staff Governance Our Network Case Studies ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Network Requirements Reviews Reports Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Reports ESnet publishes reports from science network Program Requirements Reviews on a regular basis. View the most recent of these below. Sort by: Date | Author | Type 2012 Eli Dart, Brian Tierney, Editors, "Biological and Environmental Research Network Requirements Workshop, November 2012 - Final Report"", November 29, 2012, LBNL LBNL-6395E

176

Network Communication as a Service-Oriented Capability  

SciTech Connect (OSTI)

In widely distributed systems generally, and in science-oriented Grids in particular, software, CPU time, storage, etc., are treated as"services" -- they can be allocated and used with service guarantees that allows them to be integrated into systems that perform complex tasks. Network communication is currently not a service -- it is provided, in general, as a"best effort" capability with no guarantees and only statistical predictability. In order for Grids (and most types of systems with widely distributed components) to be successful in performing the sustained, complex tasks of large-scale science -- e.g., the multi-disciplinary simulation of next generation climate modeling and management and analysis of the petabytes of data that will come from the next generation of scientific instrument (which is very soon for the LHC at CERN) -- networks must provide communication capability that is service-oriented: That is it must be configurable, schedulable, predictable, and reliable. In order to accomplish this, the research and education network community is undertaking a strategy that involves changes in network architecture to support multiple classes of service; development and deployment of service-oriented communication services, and; monitoring and reporting in a form that is directly useful to the application-oriented system so that it may adapt to communications failures. In this paper we describe ESnet's approach to each of these -- an approach that is part of an international community effort to have intra-distributed system communication be based on a service-oriented capability.

Johnston, William; Johnston, William; Metzger, Joe; Collins, Michael; Burrescia, Joseph; Dart, Eli; Gagliardi, Jim; Guok, Chin; Oberman, Kevin; O'Conner, Mike

2008-01-08T23:59:59.000Z

177

Sowmya Balasubramanian  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet in 2010. She works to develop and maintain perfSONAR (PERFormance Service Oriented Network monitoring ARchitecture), a network testing and troubleshooting system....

178

ESCC Performance Discussion - July 2010  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

PerfSONAR Update Joe Metzger, Network Engineer ESnet Network Engineering Group Summer ESCC Columbus, OH July 15, 2010 Lawrence Berkeley National Laboratory U.S. Department of...

179

Science DMZ Case Studies  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies Studies About ESnet Overview ESnet Staff Governance Our Network Case Studies OSCARS Case Studies Science DMZ Case Studies Science DMZ CU Science DMZ Penn State & VTTI Science DMZ NOAA Science DMZ NERSC Science DMZ ALS Multi-facility Workflow LCLS ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Science DMZ Case Studies Developed by ESnet engineers, the Science DMZ model addresses common network performance problems encountered at any institution by creating an environment that is tailored to the needs of high performance science

180

Recent Charmonium Physics from BES  

E-Print Network [OSTI]

Measurements of branching fractions for nine different final states, based on a data sample of approximately 4 million psi(2S) events collected with the BESI detector at the BEPC, are reported. Using the same event sample, radiative decays of the psi (2S) into pi pi, K K-bar and eta eta final states have been measured. Cross sections for e e -> e e, hadrons, pi pi J/psi, and mu mu have been measured in the vicinity of the psi(2S) resonance using the BESII detector. The psi(2S) total width; partial widths to hadrons, pi pi J/psi and muons; and corresponding branching fractions have been determined. Decays of J/psi -> gamma eta_c are used to determine the mass and width of the eta_c using a sample of 58 M J/psi events. $M_{\\eta_c} = (2977.5 \\pm 1.0 \\pm 1.2)$ MeV and $\\Gamma_{\\eta_c} = (17.0 \\pm 3.7 \\pm 7.4)$ MeV. The first observation of chicJ (J=0,1,2) decays to lambda lambda-bar is reported using psi(2S) data collected with the BESII detector. Results are compared with model predictions.

Frederick A. Harris

2003-05-30T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Collaborative Combustion Research with BES  

Broader source: Energy.gov [DOE]

2013 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting

182

Sandia National Laboratories: BES EFRC  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Doppler Velocimeter EC Top Publications A Comparison of Platform Options for Deep-water Floating Offshore Vertical Axis Wind Turbines: An Initial Study Nonlinear Time-Domain...

183

NERSC-BER-Yelick.v5.ppt  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Biological and Biological and Environmental Research Katherine Yelick NERSC Director Requirements Workshop NERSC is the Production Facility for DOE SC * NERSC serves a large population Approximately 3000 users, 400 projects, 500 code instances * Focus on "unique" resources - High end computing systems - High end storage systems * Large shared file system * Tape archive - Interface to high speed networking * ESNEt soon to be 100 Gb/s * Allocate time / storage - Current processor hours and tape storage 2 ASCR 7% BER 19% BES 29% FES 18% HEP 17% NP 10% 2009 Allocations What's Changed in DOE Priorities for NERSC? 0% 5% 10% 15% 20% 25% 30% 35% 2002 2003 2004 2005 2006 2007 2008 2009 Usage by Science Type as a Percent of Total Usage Accelerator Physics

184

Link Alpha E  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Site Environmental Restoration Program Equal Employment Opportunity Office Ergonomics eRoom Collaboration ESnet: Energy Sciences Network eSRA - Electronic System for...

185

Broadening  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Broadening the scope of optical circuit networks Malathi Veeraraghavan University of Virginia Charlottesville, VA 22904 Email: mv5g@virginia.edu Inder Monga ESnet, LBNL Berkeley,...

186

Fermilab Today  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

the Fermilab home page Unsubscribe from Fermilab Today Press Release New high-speed transatlantic network to benefit science collaborations across the U.S. ESnet will build...

187

Requirements Review Reports  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Research) Ben Allen, LANL (Bioinformatics) Greg Bell, ESnet (Networking) David Benton, GLBRCUniversity of Wisconsin (Informatics) Tom Brettin, ORNL (Bioinformatics) Shane Canon,...

188

Eli Dart  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Research) Ben Allen, LANL (Bioinformatics) Greg Bell, ESnet (Networking) David Benton, GLBRCUniversity of Wisconsin (Informatics) Tom Brettin, ORNL (Bioinformatics) Shane Canon,...

189

Attendees  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

» BER Attendees 2012 » BER Attendees 2012 About ESnet Overview ESnet Staff Governance Our Network Case Studies ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Network Requirements Reviews ASCR Requirements Review 2012 BER Requirements Review 2012 BER Attendees 2012 HEP/NP Requirements Review 2013 Documents and Background Materials FAQ for Case Study Authors Previous Reviews Reports Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net BER Attendees 2012 Attendee list for the 2012 BER Network Requirements Review Name Organization Area V. Balaji Princeton University ESGF Tom Boden ORNL ARM/CDIAC

190

Contact Us  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Contact Us Contact Us Contact Us ESnet Administration Operations Research Outreach and Communications Greg Bell Division Director Scientific Networking Division grbell@es.net Administrative Contact Shorei Butler smbutler@es.net (510) 486-6304 (510) 486-6712 [fax] Postal Address Lawrence Berkeley National Laboratory Energy Sciences Network 1 Cyclotron Road Mail stop 50A-3111 Berkeley, CA 94720 Visiting ESnet Visitor page for Lawrence Berkeley National Lab ESnet is monitored on a 24-hour-per-day basis by the ESnet networking staff located at Lawrence Berkeley National Laboratory. Our staff is available 8 a.m. to 5 p.m. P.T. Monday through Friday. Call ESnet NOC (Network Operation Center) From inside U.S.: 1 (800) 333-7638 1 (800) 33 ESnet Globally: 1 (510) 486-7600 1 (510) 486-7607

191

OSCARS helps build new circuit for JGI-NERS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Studies » OSCARS JGI Studies » OSCARS JGI About ESnet Overview ESnet Staff Governance Our Network Case Studies OSCARS Case Studies OSCARS JGI Science DMZ Case Studies Multi-facility Workflow LCLS ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net OSCARS Extends JGI Network Capacity In February 2010, the Joint Genome Institute (JGI) at Lawrence Berkeley National Laboratory (Berkeley Lab) had an immediate need for increased computing resources. Meanwhile, twenty miles away the Magellan Cloud computing cluster located at National Energy Research Scientific Computing

192

Science DMZ for ALS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ALS ALS About ESnet Overview ESnet Staff Governance Our Network Case Studies OSCARS Case Studies Science DMZ Case Studies Science DMZ CU Science DMZ Penn State & VTTI Science DMZ NOAA Science DMZ NERSC Science DMZ ALS Multi-facility Workflow LCLS ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Science DMZ for ALS Many beamline scientists at Berkeley Lab's Advanced Light Source (ALS) are or will be experiencing slower network speeds because of instrument upgrades. These new instruments, or more specifically detectors, are

193

Science DMZ National Oceanic and Atmospheric Administration  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

NOAA NOAA About ESnet Overview ESnet Staff Governance Our Network Case Studies OSCARS Case Studies Science DMZ Case Studies Science DMZ CU Science DMZ Penn State & VTTI Science DMZ NOAA Science DMZ NERSC Science DMZ ALS Multi-facility Workflow LCLS ESnet Strategic Plan ESnet Organizational Chart ESnet History Science Requirements Careers Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Science DMZ National Oceanic and Atmospheric Administration The National Oceanic and Atmospheric Administration (NOAA) in Boulder houses the Earth System Research Lab, which supports a "reforecasting" project. The initiative involves running several decades of historical

194

US LHCNet: Transatlantic Networking for the LHC and the U.S. HEP Community  

SciTech Connect (OSTI)

US LHCNet provides the transatlantic connectivity between the Tier1 computing facilities at the Fermilab and Brookhaven National Labs and the Tier0 and Tier1 facilities at CERN, as well as Tier1s elsewhere in Europe and Asia. Together with ESnet, Internet2, and other R&E Networks participating in the LHCONE initiative, US LHCNet also supports transatlantic connections between the Tier2 centers (where most of the data analysis is taking place) and the Tier1s as needed. Given the key roles of the US and European Tier1 centers as well as Tier2 centers on both continents, the largest data flows are across the Atlantic, where US LHCNet has the major role. US LHCNet manages and operates the transatlantic network infrastructure including four Points of Presence (PoPs) and currently six transatlantic OC-192 (10Gbps) leased links. Operating at the optical layer, the network provides a highly resilient fabric for data movement, with a target service availability level in excess of 99.95%. This level of resilience and seamless operation is achieved through careful design including path diversity on both submarine and terrestrial segments, use of carrier-grade equipment with built-in high-availability and redundancy features, deployment of robust failover mechanisms based on SONET protection schemes, as well as the design of facility-diverse paths between the LHC computing sites. The US LHCNet network provides services at Layer 1(optical), Layer 2 (Ethernet) and Layer 3 (IPv4 and IPv6). The flexible design of the network, including modular equipment, a talented and agile team, and flexible circuit lease management, allows US LHCNet to react quickly to changing requirements form the LHC community. Network capacity is provisioned just-in-time to meet the needs, as demonstrated in the past years during the changing LHC start-up plans.

Newman, Harvey B; Barczyk, Artur J

2013-04-05T23:59:59.000Z

195

To be published in: "Trends in High Performance & Large Scale Computing" Lucio Grandinetti and Gerhard Joubert editors, IOS Press publisher  

E-Print Network [OSTI]

and their Essential Role in Modern Science William JOHNSTON, Evangelos CHANIOTAKIS, Eli DART, Chin GUOK, Joe METZGER, Brian TIERNEY ESnet, Lawrence Berkeley National Laboratory Abstract. ESnet ­ the Energy Sciences Network ­ has the mission of enabling the aspects of the US Department of Energy's Office of Science

196

This paper is adapted from a chapter in: L. Grandinetti (ed.), "Grid Computing and New Frontiers of High Performance Processing." Elsevier, 2005.  

E-Print Network [OSTI]

, Large-Scale Science: DOE's ESnet William E. Johnston ESnet Manager and Senior Scientist, DOE Lawrence Berkeley National Laboratory, MS 50B-2239, Berkeley, California, U.S.A. Abstract Modern large-scale science. of Energy's Office of Science that examined the networking and middleware requirements of the major science

197

Visio-ESnet-4-Backbone-Peering.now.vsd  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

By: Clint Wadsworth By: Clint Wadsworth Revised: Revised by Mark Redman 06-15-2009 This Map is for DOE Business Use Only. Do Not Redistribute. For copies contact info@es.net US R&E International R&E Peering Commercial Commercial Peering International Peering OC12-Link(622Mb) NLR 10 GE Circuit Internet 2 10GE-SDN-Circuit Internet2 10GE-IP-Circuit 1GE-Link S W I T C H 10GE-Link ROUTER MAN SITE MAN 10 GE RING SITE OC48-Link(2.48Gb) OC3-Link(155Mb) FE-Link(100Mb) DS3-Link(45Mb) T1-Link(1.45Mb) Ether-Link(10Mb) R&E and International 10G Peering Connections R&E and International 1G Peering Connections PerfSonar enabled perfSONAR CANADA (CANARIE) CENIC/DREN/ INTERNET2/ LOS NETTOS/ NASA/NLR ASIA-PACIFIC (KAREN/KREONET2/NUS-GP/ ODN/REANNZ/SINET/TANET2/ TRANSPAC2) AUSTRALIA (AARnet) CENIC/INTERNET2/ LOSNETTOS/NASA

198

Historic Sudbury Neutrino Observatory Data, Carried by ESnet...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Sun) to muon or tau neutrinos. In 2001, Science Magazine identified SNO's solution to the solar neutrino mystery as one of their 10 science breakthroughs of the year. "SNO data...

199

Recent BES results and the BESIII upgrade  

E-Print Network [OSTI]

Using 58 million $J/\\psi$ and 14 million $\\psi(2S)$ events collected by the BESII detector at the BEPC, branching fractions or upper limits for the decays $J/\\psi$ and $\\psi(2S) \\to \\Lambda \\bar{\\Lambda} \\pi^0$ and $\\Lambda \\bar{\\Lambda} \\eta$ are measured, and the decays of $J/\\psi$ and $\\psi(2S)$ to $n K^0_S \\bar{\\Lambda}+c.c.$ are observed and measured for the first time. Finally, $R$ measurement data taken with the BESII detector at center-of-mass energies between 3.7 and 5.0 GeV are fitted to determine resonance parameters of the high mass charmonium states, $\\psi(3770)$, $\\psi(4040)$, $\\psi(4160)$, and $\\psi(4415)$. The Beijing Electron Collider is being upgraded to a two-ring collider (BEPCII) with a design luminosity of $1 \\times 10^{33}$cm$^{-2}$ s$^{-1}$ at 3.89 GeV and will operate between 2 and 4.2 GeV in the center of mass. With this luminosity, the new BESIII detector will beable to collect, for example, 10 billion $J/\\psi$ events in one year of running. BEPCII and BESIII are currently nearing completion, and commissioning of both is expected to begin in mid-2008.

Frederick A. Harris

2007-12-17T23:59:59.000Z

200

BES Results on Charmonium Decays and Transitions  

E-Print Network [OSTI]

Results are reported based on samples of 58 million $J/\\psi$ and 14 million $\\psi(2S)$ decays obtained by the BESII experiment. Improved branching fraction measurements are determined, including branching fractions for $J/\\psi\\to\\pi^+\\pi^-\\pi^0$, $\\psi(2S)\\to \\pi^0 J/\\psi$, $\\eta J/\\psi$, $\\pi^0 \\pi^0 J/\\psi$, anything $J/\\psi$, and $\\psi(2S)\\to\\gamma\\chi_{c1},\\gamma\\chi_{c2}\\to\\gamma\\gamma\\jpsi$. Using 14 million $\\psi(2S)$ events, $f_0(980)f_0(980)$ production in $\\chi_{c0}$ decays and $K^*(892)^0\\bar K^*(892)^0$ production in $\\chi_{cJ}~(J=0,1,2)$ decays are observed for the first time, and branching ratios are determined.

Frederick A. Harris

2004-09-29T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Experimental charmonium decay results from BES  

E-Print Network [OSTI]

Based on 14 million psi(2S) and 58 million J/psi events collected by the BESII detector, the leptonic decay of psi(2S) into $\\tau^+\\tau^-$, psi(2S) multi-body decays, chi_cJ decays, and J/psi hadronic decays are studied, and the branching fractions of these decays are reported. These results may shed light on the understanding of QCD.

Ping Rong-Gang; F. A. Harris; for BES collaboration

2007-11-23T23:59:59.000Z

202

BES2017-v2.10  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

t heir g oals a nd r each B ES r esearch o bjectives. 2. Users w ill n eed a ssistance f rom N ERSC t o p repare f or C ori ( NERSC---8) a nd f ollow---on manycore s ystems. 3....

203

ESCC  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

requesting site-specific network changes, and supplying ESnet with: The email of a site security contact who can quickly react to incident reports A network operations contact for...

204

Supercomputers Capture Turbulence in the Solar Wind  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Supercomputers Capture Supercomputers Capture Turbulence in the Solar Wind News & Publications ESnet in the News ESnet News Media & Press Publications and Presentations Galleries ESnet Awards and Honors Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Supercomputers Capture Turbulence in the Solar Wind Berkeley Lab visualizations could help scientists forecast destructive space weather December 16, 2013 | Tags: ESnet News, National Energy Research Scientific Computing Linda Vu, +1 510 495 2402, lvu@lbl.gov eddies1.jpg This visualization zooms in on current sheets revealing the "cascade of turbulence" in the solar wind occurring down to electron scales. This is

205

Services  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Services Services Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Services ESnet provides interoperable, effective, reliable, and high performance network communications infrastructure, and certain collaboration services, in support of the Office of Science (SC)'s large-scale, collaborative science programs. ESnet provides users with high bandwidth access to DOE sites and DOE's primary science collaborators including Research and

206

Elizabeth Bautista  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and security of NERSC's High Performance Systems, data storage systems and of the Energy Sciences Network (ESnet http:www.es.net). Since joining NERSC in 1999, she has...

207

Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks  

E-Print Network [OSTI]

Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks #12;Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization 1 Artificial Neural Networks Properties Applications Classical Examples Biological Background 2

Kjellström, Hedvig

208

Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks  

E-Print Network [OSTI]

Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization Artificial Neural Networks Artificial Neural Networks Single Layer Networks Multi Layer Networks Generalization 1 Artificial Neural Networks Properties Applications Classical Examples Biological Background 2 Single Layer

Kjellström, Hedvig

209

DOE Grids Service Transition  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

DOE Grids Service Transition DOE Grids Service Transition Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net DOE Grids Service Transition Background ESnet has decided to transition support and management for the certificate services provided by the DOE Grids public key infrastructure (PKI) to the Open Sciences Grid (OSG). OSG and ESnet provide service to many of the same user communities, and have long been collaborators in the areas of identity

210

Network Programming 1 Computer Networks  

E-Print Network [OSTI]

Network Programming 1 Computer Networks client/server architecture, protocols, and sockets 2;Network Programming 1 Computer Networks client/server architecture, protocols, and sockets 2 Network;client/server architecture Client/server architecture defines the communication between two computers

Verschelde, Jan

211

Publications and Presentations  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Publications and Presentations News & Publications ESnet in the News ESnet News Publications and Presentations Galleries ESnet Awards and Honors Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Publications and Presentations Sort by: Date | Author | Type 2013 Dart E., Rotman L., Tierney B., Hester M., and Zurawski J., "The Science DMZ: A Network Design Pattern for Data-Intensive Science", IEEE/ACM Annual SuperComputing Conference (SC13), Denver CO, USA, November 19, 2013, LBNL LBNL-6366E Download File: sc13sciDMZ-final.pdf (pdf: 952 KB) Ezra Kissel, Martin Swany, Brian Tierney and Eric Pouyoul, "Efficient

212

A 100-Gigbit Highway for Science  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

A 100-Gigabit Highway for A 100-Gigabit Highway for Science News & Publications ESnet in the News ESnet News Media & Press Publications and Presentations Galleries ESnet Awards and Honors Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net A 100-Gigabit Highway for Science Researchers Take a "Test Drive" on ANI Testbed April 30, 2012 | Tags: Advanced Network Initiative (ANI) Linda Vu, lvu@lbl.gov, +1 510 495 2402 A warming climate will likely change the statistics of tropical cyclones and hurricanes. This image represents one frame from a simulation called "Hurricane Season" that was created to study how well NCAR's Community

213

Cognitive Radio Networks as Sensor Networks  

E-Print Network [OSTI]

is used, assuming the cognitive radios know their ownfor Embedded Networked Sensing Cognitive Radio Networks AsJ. Pottie Introduction: Cognitive Radio (CR) Networks The

Bandari, Dorna; Yang, Seung R.; Zhao, Yue; Pottie, Gregory

2007-01-01T23:59:59.000Z

214

Year 1 Progress Report Computational Materials and Chemical Sciences Network Administration  

SciTech Connect (OSTI)

This document reports progress on the project Computational Materials and Chemical Sciences Network Administration, which is supported by DOE BES Grant DE-FG02-02ER45990 MOD 08. As stated in the original proposal, the primary goal of this project is to carry out the scientific administrative responsibilities for the Computational Materials and Chemical Sciences Network (CMCSN) of the U.S. Department of Energy, Office of Basic Energy Sciences. These responsibilities include organizing meetings, publishing and maintaining CMCSNs website, publishing a periodic newsletter, writing original material for both the website and the newsletter, maintaining CMCSN documentation, editing scientific documents, as needed, serving as liaison for the entire Network, facilitating information exchange across the network, communicating CMCSNs success stories to the larger community and numerous other tasks outside the purview of the scientists in the CMCSN. Given the dramatic increase in computational power, advances in computational materials science can have an enormous impact in science and technology. For many of the questions that can be addressed by computation there is a choice of theoretical techniques available, yet often there is no accepted understanding of the relative strengths and effectiveness of the competing approaches. The CMCSN fosters progress in this understanding by providing modest additional funding to research groups which engage in collaborative activities to develop, compare, and test novel computational techniques. Thus, the CMCSN provides the glue money which enables different groups to work together, building on their existing programs and expertise while avoiding unnecessary duplication of effort. This includes travel funding, partial postdoc salaries, and funding for periodic scientific meetings. The activities supported by this grant are briefly summarized below.

Rehr, John J.

2012-08-02T23:59:59.000Z

215

Network Perspectives on Communities  

E-Print Network [OSTI]

W W. Networks Fields and Organizations: Micro-Dynamics Scaleentitled Networks, Fields and Organizations: Micro-

Wolfe, Alvin W

2006-01-01T23:59:59.000Z

216

Better networking  

Science Journals Connector (OSTI)

... world' network means that it can be crossed in a few hops. But, reports John Whitfield, it's not necessarily easy to find the best route. It's all ...

John Whitfield

2000-08-24T23:59:59.000Z

217

Network Embedded Systems Sensor Networks  

E-Print Network [OSTI]

Link Network Transport Application SPIN BroadcastStorm TinyOS0.6 WooMAC GAF S-MAC AlohaPS PSFQ GDI CODA

Amir, Yair

218

100 Gbps Test Link Sets Pace for Faster Trans-Atlantic Data Transfers  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

100 Gbps Test Link Sets Pace for Faster Trans-Atlantic Data Transfers News & Publications ESnet in the News ESnet News Media & Press Publications and Presentations Galleries ESnet...

219

Virtual Circuits (OSCARS)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Virtual Circuits (OSCARS) Virtual Circuits (OSCARS) Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Virtual Circuits (OSCARS) ESnet's On-Demand Secure Circuits and Advance Reservation System (OSCARS) provides multi-domain, high-bandwidth virtual circuits that guarantee end-to-end network data transfer performance. Originally a research concept, OSCARS has grown into a robust production service. Currently

220

DavenportNERSC-BES-10-8-2013.ppt  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Production Research and Production Research and Storage Requirements for Basic energy Sciences October 8, 2013 Jim Davenport Program Manager - Theoretical Condensed Matter Physics Office of Basic Energy Sciences Materials R esearch i s S upported b Secretary Ernest Moniz Deputy Secretary Daniel B. Poneman Defense Nuclear Security Naval Reactors Defense Programs Counter-terrorism Emergency Operations Office of Science Vacant Patricia Dehmer (A) Nuclear Physics Tim Hallman Advanced Scientific Computing Research Steve Binkley Nuclear Energy Pete Lyons Fossil Energy Christopher Smith (A) Energy Efficiency & Renewable Energy David Danielson Basic Energy Sciences Harriet Kung High Energy Physics James Siegrist Fusion Energy Sciences Ed Synakowski Biological & Environmental Research

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

NERSC/DOE BES Requirements Workshop Worksheet - Thomas Devereaux  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

by a discrete Hubbard-Stratonovich transformation which introduces an auxiliary Ising field of size NxL, reducing the problem to a classical Monte Carlo sampling of this...

222

DOE-BES Chemical Sciences Highlights of Progress in Separations...  

Office of Science (SC) Website

nuclear weapons dating back to the Manhattan Project, are being stored in underground tanks at USDOE sites such as Hanford and Savannah River. There is currently a search for a...

223

NERSC/DOE BES Requirements Workshop Worksheet - Greg Newman  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

invert both large scale seismic and EM data sets. To insure both data sets has similar spatial resolution, sesimic data will be Laplace-Fourier transformed before before...

224

BES Results on J/psi decays and Charmonium Transitions  

E-Print Network [OSTI]

Results are reported based on samples of 58 million $\\jpsi$ and 14 million $\\psip$ decays obtained by the BESII experiment. Improved branching fraction measurements are determined, including branching fractions for $\\jpsi\\to\\ppp$, $\\psip\\ra \\pi^0\\J$, $\\eta\\J$, $\\pi^0 \\pi^0 J/\\psi$, anything $J/\\psi$, and $\\psi(2S)\\ar\\gamma\\chi_{c1},\\gamma\\chi_{c2}\\ar\\gamma\\gamma\\jpsi$. The decay $J/\\psi \\to \\omega \\pi ^+\\pi ^-$ is studied. At low $\\pi \\pi$ mass, a large, broad peak due to the $\\sigma$ is observed, and its pole position is determined. Results are presented on $\\psi(2S)$ and $J/\\psi$ hadronic decays to $K^0_SpK^-\\bar n$ and $K^0_S\\bar p K^+n$ final states. No significant $\\Theta(1540)$ signal, the pentaquark candidate, is observed, and upper limits are set. An enhancement near the $m_p + M_{\\Lambda}$ mass threshold is observed in the $p\\bar{\\Lambda}$ invariant mass spectrum from $J/\\psi \\to p K^- \\bar{\\Lambda} + c.c.$ decays. It can be fit with an S-wave Breit-Wigner resonance with a mass $m=2075\\pm 12 (stat) \\pm 5 (syst)$ MeV and a width of $\\Gamma =90 \\pm 35 (stat) \\pm 9 (syst)$ MeV.

Frederick A. Harris

2004-07-20T23:59:59.000Z

225

NERSC/DOE BES Requirements Workshop Worksheet - Jeffrey B. Neaton  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

study of light-matter interactions and charge transport --key processes fundamental to solar energy conversion -- in the following three contexts: (a) nonequilibrium charge...

226

BES Reports | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

for Efficient Energy Conversion (CNEEC) 2009-2014 University of Michigan Peter F. Green Center for Solar and Thermal Energy Conversion (CSTEC) 2009-2014 Sandia National...

227

BES_NERSC_Workshop_Final_P6.pptx  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Defect
Physics
of
Structural
Materials
for
Energy Defect
Physics
of
Structural
Materials
for
Energy 
 
Ab
initio
methods
for
simulating
the
structure,
interactions
and
 dynamics
of
defects
in
structural
materials
for
extreme
 environments 
 G. Malcolm Stocks, Don M. Nicholson, Markus Eisenbach, Paul Kent, Aurelian Rusanu, Fernando Reboredo, Randy Hood (LLNL), Jeongnim Kim (NCSA) Energy Frontier Center for Defect Physics in Structural Materials (CDP) Oak Ridge National Laboratory Thanks to: Easo George, Ben Larson, Gene Ice, Roger Stoller, Yuri Osetskiy, Steve Zinkle, Rad Radhakrishnan Project
Overview 
 "Crystals are like people: it is the defects in them that make them interesting" Sir Charles Frank  Collective effects of defects determine real materials properties

228

Network Interventions  

Science Journals Connector (OSTI)

...Identifying influential young people to undertake effective...a network tailored substance abuse prevention program among...Rice, J. E. Katz, The Internet and Health Communication: Experience...National Institute on Alcohol Abuse and Alcoholism). I thank...

Thomas W. Valente

2012-07-06T23:59:59.000Z

229

PowerPoint Presentation  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Hot Interconnects, August 18, 2005, Palo Alto, California Hot Interconnects, August 18, 2005, Palo Alto, California -1- IEEE Hot Interconnects August 18, 2005 ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) Chin Guok (chin@es.net) IEEE Hot Interconnects, August 18, 2005, Palo Alto, California -2- OSCARS: Guaranteed Bandwidth Service QoS - New Network Service * New network services are critical for ESnet to meet the needs of large-scale science like the LHC. * Most important new network service is dynamically provisioned virtual circuits that provide:

230

Neural Networks  

SciTech Connect (OSTI)

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing information [2]. Each one of these cells acts as a simple processor. When individual cells interact with one another, the complex abilities of the brain are made possible. In neural networks, the input or data are processed by a propagation function that adds up the values of all the incoming data. The ending value is then compared with a threshold or specific value. The resulting value must exceed the activation function value in order to become output. The activation function is a mathematical function that a neuron uses to produce an output referring to its input value. [8] Figure 1 depicts this process. Neural networks usually have three components an input, a hidden, and an output. These layers create the end result of the neural network. A real world example is a child associating the word dog with a picture. The child says dog and simultaneously looks a picture of a dog. The input is the spoken word ''dog'', the hidden is the brain processing, and the output will be the category of the word dog based on the picture. This illustration describes how a neural network functions.

Smith, Patrick I.

2003-09-23T23:59:59.000Z

231

Networking from a network coding perspective  

E-Print Network [OSTI]

Network coding generalizes network operation beyond traditional routing, or store-and-forward, approaches, allowing for mathematical operations across data streams within a network. This thesis considers a number of ...

Ho, Tracey, 1976-

2004-01-01T23:59:59.000Z

232

Network Connections  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Connecting to NERSC Using X Windows Connecting to NERSC with NX Transferring Data Network Performance Queues and Scheduling Job Logs & Analytics Training & Tutorials Software Accounts & Allocations Policies Data Analytics & Visualization Data Management Policies Science Gateways User Surveys NERSC Users Group User Announcements Help Operations for: Passwords & Off-Hours Status 1-800-66-NERSC, option 1 or 510-486-6821 Account Support https://nim.nersc.gov accounts@nersc.gov 1-800-66-NERSC, option 2 or 510-486-8612 Consulting http://help.nersc.gov consult@nersc.gov 1-800-66-NERSC, option 3 or 510-486-8611 Home » For Users » Network Connections Network Connections NERSC's resources can be accessed using SSH and related tools, grid tools, and via the web. This section explains how to connect to NERSC

233

Tourism networks and computer networks  

E-Print Network [OSTI]

The body of knowledge accumulated in recent years on the structure and the dynamics of complex networks has offered useful insights on the behaviour of many natural and artificial complex systems. The analysis of some of these, namely those formed by companies and institutions, however, has proved problematical mainly for the difficulties in collecting a reasonable amount of data. This contribution argues that the World Wide Web can provide an efficient and effective way to gather significant samples of networked socio-economic systems to be used for network analyses and simulations. The case discussed refers to a tourism destination, the fundamental subsystem of an industry which can be considered one of the most important in today's World economy.

Baggio, Rodolfo

2008-01-01T23:59:59.000Z

234

Presentations  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

A User Driven Dynamic Circuit Network Implementation A User Driven Dynamic Circuit Network Implementation November 30, 2008 | Author(s): Evangelos Chaniotakis | Download File: oscars-danms2008-v1.ppt | ppt | 1.5 MB DANMS, Nov 30 2008, New Orleans, LA ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) 031406 March 14, 2006 | Author(s): Chin Guok | Download File: oscars-uclp-20060316.pdf | pdf | 102 KB UCLPv2 Workshop 2; March 14-16, 2006 ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) 051506 May 15, 2006 | Author(s): Chin Guok, David Robertson | Download File: oscars-quilt-20060516.pdf | pdf | 114 KB QUILT; May 15-16, 2006 ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) 081805 August 18, 2005 | Download File: oscars-ieee-20050818.pdf | pdf | 152 KB

235

Terms and Conditions  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Terms and Conditions Terms and Conditions R&D Overview 100G Testbed Testbed Description Testbed Results Current Testbed Research Proposal Process Terms and Conditions Virtual Circuits (OSCARS) Performance (perfSONAR) Tools Development Green Networking Authentication & Trust Federation (ATF) Partnerships Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Terms and Conditions Researchers must provide ESnet copies of any articles, presentations, and publications based on testbed research for posting on the ESnet Testbed web site. All publications based on work conducted on the testbed must include the following statement:

236

Hybrid artificial neural network  

Science Journals Connector (OSTI)

Artificial neural networks (ANNs) or simply neural networks (NNs) are now a consolidated technique ... , and simulate the behavior of the biological neural network in a human brain. For that purpose ... use a sta...

Nadia Nedjah; Ajith Abraham; Luiza M. Mourelle

2007-05-01T23:59:59.000Z

237

Artificial Neural Network  

Science Journals Connector (OSTI)

An artificial neural network (with acronym ANN), usually addressed as neural network (with acronym NN), is a model ... the structure and/or functional aspects of biological neural networks or human brain. A neural

Dr. Gmez Gonzlez Daniel

2013-01-01T23:59:59.000Z

238

ASCR Science Network Requirements  

E-Print Network [OSTI]

ASCR Science Network Requirements Office of AdvancedScientific Computing Research, DOE Office of ScienceEnergy Sciences Network Gaithersburg, MD April 15 and 16,

Dart, Eli

2010-01-01T23:59:59.000Z

239

Energy Efficient Networks  

Science Journals Connector (OSTI)

Optical networks are at the center of efforts to achieve sustainable Internet growth. Techniques for modeling energy use in networks are reviewed along with results of recent research...

Kilper, Dan

240

Network coding for robust wireless networks  

E-Print Network [OSTI]

Wireless networks and communications promise to allow improved access to services and information, ubiquitous connectivity, and mobility. However, current wireless networks are not well-equipped to meet the high bandwidth ...

Kim, MinJi, Ph. D. Massachusetts Institute of Technology

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

RDP Neural Network RDP Neural Network Construction Principle  

E-Print Network [OSTI]

for building RDP Neural Networks Geometrical Approaches for Artificial Neural Networks David Elizondo Centre Elizondo Geometrical Approaches for Artificial Neural Networks #12;RDP Neural Network RDP Neural Network David Elizondo Geometrical Approaches for Artificial Neural Networks #12;RDP Neural Network RDP Neural

Gorban, Alexander N.

242

Dynamic NetworksDynamic Networks ApplicationsApplications  

E-Print Network [OSTI]

Satellite Constellation Network #12;Satellite and Undersea Cable Networks #12;Energy NetworksEnergy Networks Electric Power Network #12;Duke Energy Gas Pipeline Network #12;Components of Some Common Physical Networks Roads, Airline Routes, Railroad Track Automobiles, Trains, and Planes, Manufacturing and logistics

Nagurney, Anna

243

Network Algorithms (Lecture Notes)  

E-Print Network [OSTI]

Network Algorithms (Lecture Notes) Dr. Stefan Schmid Thanks to Prof. Dr. Roger Wattenhofer and Prof to the Network Algorithms course! Computer systems are becoming more distributed and networked. This has two main, in order to fully exploit the distributed resource network, efficient algorithms need to be designed

Schmid, Stefan

244

Professional Networking Michelle Burdick  

E-Print Network [OSTI]

Development Green Sustainability Professionals #12;How To Use LinkedIn Groups Group Discussions: ­ Members can Environmental Careers Network GIS Professional & Networking Green Jobs & Career Network Sustainable EnergyLinkedIn Professional Networking Workshop Michelle Burdick 24 January 2014 #12;· Building a Strong

Awtar, Shorya

245

Networks, Information & Social Capital  

E-Print Network [OSTI]

This paper investigates how information flows enable social networks to constitute social capital. By analyzing

Aral, Sinan

2008-01-26T23:59:59.000Z

246

E-Print Network 3.0 - area network performance Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

networks - network performance modeling - wireless networks - wireless sensor networks - ad hoc ... Source: Iowa State University, Office of Biorenewables Programs Collection:...

247

Online Submission ID: 0 Detecting Distributed Scans Using High-Performance Query-Driven  

E-Print Network [OSTI]

and destination ports, duration of connection, number of bytes exchanged and so forth. A year's worth of such data and Johnston 2005], traffic volume over ESnet, a production network servicing the U. S. Department of Energy analyzed. For example, to identify unusual activities on TCP ports, we may compute a histogram over

Geddes, Cameron Guy Robinson

248

Building a Network Simulation Model of the Teragrid Network  

E-Print Network [OSTI]

Building a Network Simulation Model of the Teragrid Network Thomas Hacker Preston Smith* Computer in designing and using an accurate network simulation model of the Teragrid network, and the performance

Jiang, Wen

249

Morphological neural networks  

SciTech Connect (OSTI)

The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

1996-12-31T23:59:59.000Z

250

Network coded wireless architecture  

E-Print Network [OSTI]

Wireless mesh networks promise cheap Internet access, easy deployment, and extended range. In their current form, however, these networks suffer from both limited throughput and low reliability; hence they cannot meet the ...

Katti, Sachin Rajsekhar

2008-01-01T23:59:59.000Z

251

Financial Networks Anna Nagurney  

E-Print Network [OSTI]

themselves, such as the Internet with electric power networks, financial networks, and transportation Automobiles, Trains, and Planes, Manufacturing and logistics Workstations, Distribution Points Processing Cables Radio Links Voice, Data, Video Energy Pumping Stations, Plants Pipelines, Transmission Lines Water

Nagurney, Anna

252

Energy Efficient Digital Networks  

E-Print Network [OSTI]

Energy Use of Network Equipment, by Device Type (TWh) Power (W) Market Segment (Measurement Units)Energy Use of Network Equipment, by Device Type (TWh) Power (W) Market Segment (Measurement Unit)

Lanzisera, Steven

2014-01-01T23:59:59.000Z

253

Probabilistic Biological Network Alignment  

Science Journals Connector (OSTI)

Interactions between molecules are probabilistic events. An interaction may or may not happen with some probability, depending on a variety of factors such as the size, abundance, or proximity of the interacting molecules. In this paper, we consider ... Keywords: Probabilistic logic,Proteins,Network topology,Polynomials,Random variables,Topology,random graphs,Probabilistic biological networks,network alignment,neighborhood topology

Andrei Todor; Alin Dobra; Tamer Kahveci

2013-01-01T23:59:59.000Z

254

Networks within networks - interaction in bioenergy business  

Science Journals Connector (OSTI)

Collaboration is seen as one of the most important means for small and medium-sized enterprises (SMEs) to compete and innovate in dynamic business environments. This paper approaches this phenomenon by studying a group of Finnish biomass heating firms and their interaction in the bioenergy business. In this paper, two frameworks are combined into a practical two-level tool for relationship and network analysis. This paper offers detailed information on the formation of partnerships and networks around the bioenergy business. Moreover, it speculates about the motives and mechanisms behind an actor's business relations. This study confirms that it is often profitable for SMEs to act simultaneously in different types of networks. In these networks, the firms form relationships that are different in breadth and depth.

Kirsi Kokkonen; Tuomo Kässi; Ville Ojanen

2014-01-01T23:59:59.000Z

255

Random Walks and Electrical Networks Electrical Network ...  

E-Print Network [OSTI]

Feb 4, 2008 ... Much of this talk is based on the book Random Walks and Electric. Networks by Peter .... Rx,y resistance of the edge from x to y. Cx,y = 1. Rx,y.

Jonathon Peterson

2008-01-30T23:59:59.000Z

256

Faster information dissemination in dynamic networks via network coding  

E-Print Network [OSTI]

We use network coding to improve the speed of distributed computation in the dynamic network model of Kuhn, Lynch and Oshman [STOC '10]. In this model an adversary adaptively chooses a new network topology in every round, ...

Haeupler, Bernhard

257

Handbook of Network Analysis [KONECT -- the Koblenz Network Collection  

E-Print Network [OSTI]

This is the Handbook of Network Analysis, the companion article to the KONECT (Koblenz Network Collection) project. This project is intended to collect network datasets, analyse them systematically, and provide both datasets and the underlying network analysis code to researchers. This article outlines the project, gives all definitions used within the project, reviews all network statistics used, reviews all network plots used, and gives a brief overview of the API used by KONECT.

Kunegis, Jrme

2014-01-01T23:59:59.000Z

258

From Photo Networks to Social Networks, Creation and Use of a Social Network Derived with Photos  

E-Print Network [OSTI]

From Photo Networks to Social Networks, Creation and Use of a Social Network Derived with Photos and photos have received plenty of attention in the digital age. In this paper, we show how social photos that reveals social attributes. From this photo network, a social network is extracted that can help to build

Boyer, Edmond

259

Rooftop Unit Network Project  

Broader source: Energy.gov (indexed) [DOE]

Network Project Network Project RTU Network Project Michael Brambley, Ph.D. Pacific Northwest National Laboratory Michael.Brambley@pnnl.gov (509) 375-6875 April 4, 2013 2 | Building Technologies Office eere.energy.gov * Packaged air conditioners and heat pumps (RTUs) are used in about 58% of all cooled commercial buildings, serving about 69% of the cooled commercial building floor space (EIA 2003) - Navigant estimates packaged A/C uses 0.9 quads of electricity for cooling annually and

260

Multiperiod Competitive Supply Chain Networks with Inventorying and A Transportation Network Equilibrium Reformulation Multiperiod Competitive Supply Chain Networks  

E-Print Network [OSTI]

Multiperiod Competitive Supply Chain Networks with Inventorying and A Transportation Network Equilibrium Reformulation Multiperiod Competitive Supply Chain Networks with Inventorying and A Transportation Competitive Supply Chain Networks with Inventorying and A Transportation Network Equilibrium Reformulation

Nagurney, Anna

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Handoff Notification in Wireless Hybrid Networks  

Science Journals Connector (OSTI)

Hybrid networks composed of a wireless infrastructure network providing Internet access to an underlying...

Guillaume Chelius; Claude Chaudet

2005-01-01T23:59:59.000Z

262

Classifying Artificial Neural Network Architecture  

Science Journals Connector (OSTI)

Most Artificial Neural Network architecture appears to be heuristic in conception; ... be preferable to develop a formal taxonomy for Neural Networks in order that network size and designs may be matched more ......

Dr J. P. Evans

1990-01-01T23:59:59.000Z

263

Home Area Networks  

Science Journals Connector (OSTI)

Indoor networks must transport a wide variety of services, and support both wirebound and wireless broadband connectivity. Architectures and techniques for cost- and energy-efficient...

Koonen, A

264

Nanotechnology for Optical Networks  

Science Journals Connector (OSTI)

Transparent optical networks will rely on electronics for control and monitoring. Integrating infrared optoelectronic devices such as lasers, modulators, and detectors onto silicon...

Sargent, Edward

265

Thermodynamics of Fractal Networks  

Science Journals Connector (OSTI)

Optimal channel networks are fractal structures that bear a striking resemblance to real rivers. They are obtained by minimizing an energy functional associated with spanning trees. We show that large network development effectively occurs at zero temperature since the entropy scales subdominantly with system size compared to the energy. Thus these networks develop under generic conditions and freeze into a static scale-free structure. We suggest a link of optimal channel networks with self-organized critical systems and critical phenomena which exhibit spatial and temporal fractality, the former under generic conditions and the latter on fine tuning.

Andrea Rinaldo; Amos Maritan; Francesca Colaiori; Alessandro Flammini; Riccardo Rigon; Ignacio Rodriguez-Iturbe; Jayanth R. Banavar

1996-04-29T23:59:59.000Z

266

BER Science Network Requirements  

E-Print Network [OSTI]

Networking) David Benton, GLBRC/University of Wisconsin (and analysis tools. GLBRC currently comprises some 44 inter-year funding period of the GLBRC, while several terabytes of

Dart, Eli

2011-01-01T23:59:59.000Z

267

The simplicity of planar networks  

E-Print Network [OSTI]

source and observe the micro-tube network at six phases ofin a planar network-like structure of micro-tubes 33 . In

Viana, Matheus P; Strano, Emanuele; Bordin, Patricia; Barthelemy, Marc

2013-01-01T23:59:59.000Z

268

Fusion Energy Sciences Network Requirements  

E-Print Network [OSTI]

Network Research) C.S. Chang, PPPL (Fusion Simulations) EliGreenwald, MIT PSFC (Alcator C-Mod) Paul Henderson, PPPL (PPPL Networking) Steve Jardin, PPPL (Fusion Simulations)

Dart, Eli

2014-01-01T23:59:59.000Z

269

Water Network Design by MINLP  

E-Print Network [OSTI]

Feb 13, 2008 ... We propose a solution method for a water-network optimization problem ... The optimal design of a WDN (Water Distribution Network) consists,...

2008-02-12T23:59:59.000Z

270

Supporting Advanced Scientific Computing Research * Basic Energy Sciences * Biological  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Monitoring and Network Monitoring and Visualiza4on at ESnet Jon Dugan, Network Engineer ESnet Network Engineering Group February 3, 2010 Winter Joint Techs, Salt Lake City, UT Overview Data Collec4on (ESxSNMP) Data Visualiza4on (Graphite) Event/Metadata Log (Net Almanac) ESxSNMP: Goals * Automate everything possible * Provide summaries but don't lose raw data - Disk is cheap - It can be useful to take a hard look at the past * Flexibility and scalability * Minimize up front assumptions * Protect data collection from DoS by users * Make data easy to access and manipulate ESxSNMP: Polling * Interface metadata - Automatically detects new interfaces - Automatically detects interface changes - Historical log of interface info * Automatic addition of new devices

271

oscars-glif-20070917.v1.0.ppt  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

ESnet On-demand ESnet On-demand Secure Circuits and Advance Reservation System (OSCARS) Chin Guok Network Engineering Group October 17 2007 Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the Future of Science 2 Requirements for Virtual Circuit Services * Identified as one of the two most important new network service by the 2002 science requirements workshop (the other being end-to-end performance monitoring) * Dynamically provisioned virtual circuits that provide: - Traffic Isolation * Will enable the use of high-performance, non-standard transport mechanisms that cannot co-exist with commodity TCP based transport. (see, e.g., Tom Dunigan's compendium http://www.csm.ornl.gov/~dunigan/netperf/netlinks.html ) - Guaranteed Bandwidth * The only way that we have currently to address deadline scheduling

272

Essays on Network Formation  

E-Print Network [OSTI]

that may depend on the network of connections among the individuals that make up each group. I assume the existence of a single divisible good, such as a monetary prize, which will be divided amongst the members of the winning network. The probability...

Mueller, William Graham

2012-10-19T23:59:59.000Z

273

Green Networking Basem Shihada  

E-Print Network [OSTI]

business areas for green networking. #12;Resource & Energy Allocation Applications Application Domains #12Green Networking Systems Basem Shihada CEMSE, KAUST Graduate Seminar Sunday Sept. 22nd 2013 #12 connectivity and load will fluctuate rapidly, both in space and time. #12;ICT Energy Consumption Trends

Shihada, Basem

274

Collective network routing  

DOE Patents [OSTI]

Disclosed are a unified method and apparatus to classify, route, and process injected data packets into a network so as to belong to a plurality of logical networks, each implementing a specific flow of data on top of a common physical network. The method allows to locally identify collectives of packets for local processing, such as the computation of the sum, difference, maximum, minimum, or other logical operations among the identified packet collective. Packets are injected together with a class-attribute and an opcode attribute. Network routers, employing the described method, use the packet attributes to look-up the class-specific route information from a local route table, which contains the local incoming and outgoing directions as part of the specifically implemented global data flow of the particular virtual network.

Hoenicke, Dirk

2014-12-02T23:59:59.000Z

275

Neural Networks and Radial Basis Functions 1. Neural network theory  

E-Print Network [OSTI]

Neural Networks and Radial Basis Functions 1. Neural network theory 1. Since artificial computational solutions to problems in intelligence 2. Neural network theory has held that promise. Existence, psychology, engineering, mathematics 3. A basic component of many neural nets: feed-forward neural networks

Kon, Mark

276

Adoption of Vehicular Ad Hoc Networking Protocols by Networked Robots  

Science Journals Connector (OSTI)

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several ... Keywords: Networked robot, Robotic ad hoc network, V2I, V2V, Vehicular ad hoc network, Wireless robot

Wim Vandenberghe; Ingrid Moerman; Piet Demeester

2012-06-01T23:59:59.000Z

277

Seminar: Ad Hoc Networks Konrad Meier Seminar Ad Hoc Networks  

E-Print Network [OSTI]

1 Seminar: Ad Hoc Networks Konrad Meier Seminar Ad Hoc Networks Feasibility of an Aeronautical Mobile Ad Hoc Network Over the North Atlantic Corridor Daniel Medina, Felix Hoffmann, Serkan Ayaz;2 What is the idea? Ad Hoc Network in the North Atlantic Corridor ­ multihop air to air communication

Schindelhauer, Christian

278

Software-Defined Networking Based Capacity Sharing in Hybrid Networks  

E-Print Network [OSTI]

Software-Defined Networking Based Capacity Sharing in Hybrid Networks Mateus A. S. Santos and Bruno proposes a novel approach to capacity sharing in hybrid networked environments, i.e., environments that consist of infrastructure-based as well as infrastructure- less networks. The proposed framework is based

Turletti, Thierry

279

New Paradigm for Seismic Networks: Crowd-Sourced Seismic Networks,  

E-Print Network [OSTI]

#12;New Paradigm for Seismic Networks: Crowd-Sourced Seismic Networks, including Buildings Tom Egill Hauksson #12;SCSN: what does it encompass? · ~360 Seismic Stations · ~60 stations from partners SCSN/SCEDC total of ~26 FTE's #12;Crowd Sourced Networks · Current broadband seismic network

Greer, Julia R.

280

all-optical telecommunications network  

Science Journals Connector (OSTI)

A telecommunications network in which (a) all signals...See also electronic , electronic signal , fib...

2001-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Centdian computation for sensor networks  

Science Journals Connector (OSTI)

This paper focuses on the centdian problem in a cactus network where a cactus network is a connected undirected graph, and any two simple cycles in the graph have at most one node in common The cactus network has important applications for wireless ... Keywords: cactus graph, centdian node, distributed algorithm, sensor network

Boaz Ben-Moshe; Amit Dvir; Michael Segal; Arie Tamir

2010-06-01T23:59:59.000Z

282

Scientists to use hybrid network  

E-Print Network [OSTI]

"European research and education network operator implements for high-speed infrastructure." (1/2 page)

Willimans, Lara

2007-01-01T23:59:59.000Z

283

LHC Network Measurement Joe Metzger  

E-Print Network [OSTI]

1 HENP SIG LHC Network Measurement Challenges Joe Metzger April 22 2008 Internet2 Spring Members #12;2 Current Network Environment · Most R&E network backbones are composed of 10Gbps links · The LHC... ­ Network topology is constantly changing! ­ LHC data transfer flows are not typical internet flows ­ Many

284

Optical Network Testbeds Workshop  

SciTech Connect (OSTI)

This is the summary report of the third annual Optical Networking Testbed Workshop (ONT3), which brought together leading members of the international advanced research community to address major challenges in creating next generation communication services and technologies. Networking research and development (R&D) communities throughout the world continue to discover new methods and technologies that are enabling breakthroughs in advanced communications. These discoveries are keystones for building the foundation of the future economy, which requires the sophisticated management of extremely large qualities of digital information through high performance communications. This innovation is made possible by basic research and experiments within laboratories and on specialized testbeds. Initial network research and development initiatives are driven by diverse motives, including attempts to solve existing complex problems, the desire to create powerful new technologies that do not exist using traditional methods, and the need to create tools to address specific challenges, including those mandated by large scale science or government agency mission agendas. Many new discoveries related to communications technologies transition to wide-spread deployment through standards organizations and commercialization. These transition paths allow for new communications capabilities that drive many sectors of the digital economy. In the last few years, networking R&D has increasingly focused on advancing multiple new capabilities enabled by next generation optical networking. Both US Federal networking R&D and other national R&D initiatives, such as those organized by the National Institute of Information and Communications Technology (NICT) of Japan are creating optical networking technologies that allow for new, powerful communication services. Among the most promising services are those based on new types of multi-service or hybrid networks, which use new optical networking technologies. Several years ago, when many of these optical networking research topics were first being investigated, they were the subject of controversial debate. The new techniques challenged many long-held concepts related to architecture and technology. However, today all major networking organizations are transitioning toward infrastructure that incorporates these new concepts. This progress has been assisted through the series of Optical Networking Testbed Workshops (ONT). The first (ONT1) outlined a general framework of key issues and topics and developed a series of recommendations (www.nren.nasa.gov/workshop7). The second (ONT2) developed a common vision of optical network technologies, services, infrastructure, and organizations (www.nren.nasa.gov/workshop8). Processes that allow for a common vision encourage widespread deployment of these types of resources among advanced networking communities. Also, such a shared vision enables key concepts and technologies to migrate from basic research testbeds to wider networking communities. The ONT-3 workshop built on these earlier activities by expanding discussion to include additional considerations of the international interoperability and of greater impact of optical networking technology on networking in general. In accordance with this recognition, the workshop confirmed that future-oriented research and development is indispensable to fundamentally change the current Internet architecture to create a global network incorporating completely new concepts. The workshop also recognized that the first priority to allow for this progress is basic research and development, including international collaborative activities, which are important for the global realization of interoperability of a new generation architecture.

Joe Mambretti

2007-06-01T23:59:59.000Z

285

E-Print Network 3.0 - ad hoc networking Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

networking Search Powered by Explorit Topic List Advanced Search Sample search results for: ad hoc networking...

286

E-Print Network 3.0 - ad hoc networks Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

networks Search Powered by Explorit Topic List Advanced Search Sample search results for: ad hoc networks...

287

E-Print Network 3.0 - ad hoc network Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

network Search Powered by Explorit Topic List Advanced Search Sample search results for: ad hoc network...

288

Detecting Network Vulnerabilities Through Graph Theoretical Methods  

E-Print Network [OSTI]

Introduction The electric power grid network is susceptibleProblem We model electric power grid networks as undirectedlines in the electric power grid network. Because of the

2007-01-01T23:59:59.000Z

289

Energy Efficiency Limits of Load Adaptive Networks  

Science Journals Connector (OSTI)

Based on traffic models the energy consumption of adaptive networks is compared to networks with constant power consumption. The results show that adaptive network resource...

Lange, Christoph; Gladisch, Andreas

290

Fact Sheet: Better Buildings Residential Network | Department...  

Broader source: Energy.gov (indexed) [DOE]

Fact Sheet: Better Buildings Residential Network Fact Sheet: Better Buildings Residential Network Fact Sheet: Better Buildings Residential Network, increasing the number of...

291

Better Buildings Residential Network Membership Form | Department...  

Broader source: Energy.gov (indexed) [DOE]

Network Membership Form Better Buildings Residential Network Membership Form Membership form from the U.S. Department of Energy's Better Buildings Residential Network Recommended...

292

Open Grid Forum  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Publications and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Engineering Services OSCARS OSCARS Standard and Open Grid Forum Engineering Services...

293

Office of the Chief Financial Officer Annual Report 2013  

E-Print Network [OSTI]

as ALS and ESnet. (e) Safeguards and Security funding movedas ALS and ESnet. (e) Safeguards and Security funding moveddue to rounding. (a) Safeguards and Security funding moved

Williams, Kim

2014-01-01T23:59:59.000Z

294

Science Requirements Process  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and Presentations Galleries ESnet Awards and Honors ESnet Live Blog Home Science Engagement Science Requirements Reviews Science Engagement Move your data Programs...

295

BSS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

BSS BSS Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers DCN/OSCARS Implementation (Aug 2007) AAA BSS Pathfinder Topology Path realization Dojo development Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net BSS Bandwidth Scheduling Subcomponent

296

Message Security  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Message Message Security Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Message Security Overview The OSCARS Web pages and Web Services are run within a Tomcat container which uses SSL connections to encrypt all messages. The OSCARS Web Service

297

Design Specifications  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Design Design Specifications Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Design Specifications OSCARS Reservation Manager - Design Specifications Year 3 Update (DRAFT) David Robertson, Chin Guok

298

For Developers  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Developers Developers Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers DCN/OSCARS Implementation (Aug 2007) AAA BSS Pathfinder Topology Path realization Dojo development Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net For Developers DCN/OSCARS Implementation (Aug 2007)

299

Notifications  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Notifications Notifications Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Notifications Configuring Notifications OSCARS includes the ability to send notifications of events that occur as

300

Web Browser Interface (WBUI)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Browser Interface (WBUI) Browser Interface (WBUI) Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual Web Browser Interface (WBUI) Web Service Interface (API) FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Web Browser Interface (WBUI) 1. Login Before you can access the server you must login using the user name that

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Functional Specifications  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Functional Specifications Functional Specifications Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Functional Specifications OSCARS Reservation Manager - Functional Specifications Year 3 Update (DRAFT)

302

Authorization Policy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Authorization Policy Authorization Policy Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Authorization Policy Introduction An authorization decision consists of deciding if an authenticated entity

303

User Manual  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Manual Manual Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual Web Browser Interface (WBUI) Web Service Interface (API) FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net User Manual Introduction The OSCARS Interdomain Controller (IDC) allows end users to reserve high

304

Pathfinder  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Pathfinder Pathfinder Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers DCN/OSCARS Implementation (Aug 2007) AAA BSS Pathfinder Topology Path realization Dojo development Interfaces Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Pathfinder Pathfinder component notes

305

Wireless Sensor Network Fundamentals  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Wireless Sensor Network Fundamentals Wireless Sensor Network Fundamentals Speaker(s): Steven Lanzisera Date: February 8, 2010 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Kevin Kircher Wireless sensor networks have been promising to provide easy data collection and control capability to applications ranging from scientific data collection, disaster recover, national security, and more. The user experience, however, has been filled with confusing terminology, complicated systems, and a lack of interoperability between vendors. Users with a background in the technology and fundamentals are better able to understand system capabilities, make decisions, and end up with a network that meets their needs. Although a sufficient coverage of this topic is at least a semester course, the goal of this talk is to give a brief

306

Valley Network (Venus)  

Science Journals Connector (OSTI)

Labyrinthic valley network (Fig. 1...). This is the most common type observed on Venus. Valleys are several km wide and 100 s km long. They are found within or near tectonically...1992, 1993, 2001...). Their morp...

Goro Komatsu

2014-06-01T23:59:59.000Z

307

Architecting space communication networks  

E-Print Network [OSTI]

Reliable communication and navigation services are critical to robotic and human space missions. NASA currently provides them through three independent and uncoordinated network that consist of both Earth-based and space-based ...

Sanchez Net, Marc

2014-01-01T23:59:59.000Z

308

Optimization in Networks  

E-Print Network [OSTI]

The recent surge in the network modeling of complex systems has set the stage for a new era in the study of fundamental and applied aspects of optimization in collective behavior. This Focus Issue presents an extended view of the state of the art in this field and includes articles from a large variety of domains where optimization manifests itself, including physical, biological, social, and technological networked systems.

Adilson E. Motter; Zoltan Toroczkai

2007-07-07T23:59:59.000Z

309

Digital Networks: Electronics and Beyond  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Digital Networks: Electronics and Beyond Digital Networks: Electronics and Beyond Speaker(s): Bruce Nordman Date: January 9, 2009 - 12:00pm Location: 90-3122 For the last five years or so, I have made digital networks my prime research focus. For the most part, this has concentrated on IT networks as with PCs and servers, and the network interfaces and network devices that enable it. I will outline how to think about networks as they collide with energy use and efficiency, and report on the several projects we have underway in this area. Networks have a unique relationship to industry standards and I will outline some of the challenges and opportunities this brings. In addition, we have the looming prospect of the networking of many non-electronic loads in buildings (particularly lighting and climate

310

Aircraft System Identification Using Artificial Neural Networks  

E-Print Network [OSTI]

Aircraft System Identification Using Artificial Neural Networks Kenton Kirkpatrick , Jim May Jr Artificial Neural Network System Identification, has the advantages of being straightforward with low for aircraft using an artificial neural network (ANN). Artificial neural networks are useful for creating

Valasek, John

311

Enhancing opportunistic networks with legacy nodes  

Science Journals Connector (OSTI)

Mobile opportunistic networking utilizes device-to-device communication to provide messaging and content sharing mechanisms between mobile users without the need for supporting infrastructure networks. However, enabling opportunistic networking in practice ... Keywords: cookies, dtn, http, opportunistic networking, web storage

Marcin Nagy, Teemu Krkkinen, Jrg Ott

2014-09-01T23:59:59.000Z

312

Vulnerability Analysis of Complex Networks from Transportation Networks to  

E-Print Network [OSTI]

, Satellites, Telephone Exchanges Fiber Optic Cables Radio Links Voice, Data, Video Energy Pumping Stations Grid Transportation, Communication, and Energy Networks #12;Components of Common Physical Networks, Plants Pipelines, Transmission Lines Water, Gas, Oil, Electricity #12;US Railroad Freight Flows #12

Nagurney, Anna

313

Better Buildings Network View | November 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

314

Better Buildings Network View | October 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

315

Better Buildings Network View | September 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

316

Better Buildings Network View | January 2015  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

317

In Vitro Perfused Human Capillary Networks  

E-Print Network [OSTI]

during vessel network formation, micro- spheres traversedof a living network of dynamic human capillaries in a micro-

Moya, Monica L.; Hsu, Yu-Hsiang; Lee, Abraham P.; Hughes, Christopher C.W.; George, Steven C.

2013-01-01T23:59:59.000Z

318

Better Buildings Network View | December 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

319

Better Buildings Network View | February 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

320

Better Buildings Network View | April 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Better Buildings Network View | May 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

322

Better Buildings Network View | March 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

323

Instructions for Using Virtual Private Network (VPN)  

Broader source: Energy.gov [DOE]

Virtual Private Network (VPN) provides access to network drives and is recommended for use only from a EITS provided laptop.

324

Better Buildings Network View | June 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

325

Autonomic behaviour of opportunistic network routing  

Science Journals Connector (OSTI)

In opportunistic networks, end-to-end communication among users does not require a continuous end-to-end path between source and destination. Network protocols are designed to be extremely resilient to events such as long partitions, ... Keywords: autonomic communication, context-aware routing, delay-tolerant networks, mobile networks, opportunistic networks, self-organising networks

Chiara Boldrini; Marco Conti; Andrea Passarella

2008-07-01T23:59:59.000Z

326

SG Network System Requirements Specification  

Broader source: Energy.gov (indexed) [DOE]

SG Network System Requirements Specification SG Network System Requirements Specification Interim Release 3 5/17/2010 - 2 - Table of Contents Document History ....................................................................................................................................... - 3 - Revision History .......................................................................................................................................... - 3 - Preface........................................................................................................................................................ - 4 - Authors........................................................................................................................................................ - 6 -

327

Mobility in Wireless Sensor Networks  

E-Print Network [OSTI]

A MAV D C ADV E D Micro Air Vehicle Network Manager C B D CA B A F A D B A E Micro Air Vehicle Network Manager C B MAV

Mehta, Ankur Mukesh

2012-01-01T23:59:59.000Z

328

Energy Consumption in Access Networks  

Science Journals Connector (OSTI)

We present a comparison of energy consumption of access networks. We consider passive optical networks, fiber to the node, point-to-point optical systems and WiMAX. Optical access...

Baliga, Jayant; Ayre, Robert; Sorin, Wayne V; Hinton, Kerry; Tucker, Rodney S

329

Network coding for anonymous broadcast  

E-Print Network [OSTI]

This thesis explores the use of network coding for anonymous broadcast. Network coding, the technique of transmitting or storing mixtures of messages rather than individual messages, can provide anonymity with its mixing ...

Sergeev, Ivan A

2013-01-01T23:59:59.000Z

330

Can Neural Networks Explain Stuttering?  

Science Journals Connector (OSTI)

Recently, neural networks have received a great deal of attention from various disciplines. [1,2] In medicine neural network technology is considered helpful both as a new way of constructing systems for clini...

Maikl Braamhof

1990-01-01T23:59:59.000Z

331

Video transmission over wireless networks  

E-Print Network [OSTI]

Compressed video bitstream transmissions over wireless networks are addressed in this work. We first consider error control and power allocation for transmitting wireless video over CDMA networks in conjunction with multiuser detection. We map a...

Zhao, Shengjie

2005-08-29T23:59:59.000Z

332

Green Networks: Energy Efficient Design for Optical Networks Balagangadhar G. Bathula, Jaafar M. H. Elmirghani  

E-Print Network [OSTI]

Green Networks: Energy Efficient Design for Optical Networks Balagangadhar G. Bathula, Jaafar M. H in backbone networks such as optical networks increase. Energy consumption of optical networks is an important the energy consumption of optical networks. We propose sleep cycle protocols for use in the network nodes

Bathula, Balagangadhar G

333

Computers and Computer Networks  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and Computer Networks and Computer Networks Computer Science documentation, etc. Computer Science Research and Services at the Lab Super Computing Computer Graphics Computer & Internet information via yahoo.com, categorized by subject Perl UNIX documentation Shareware sites MBONE and Videoconferencing Computer Networks and related documentation Computer Documentation World Wide Web UNIX Documentation TeX, LaTeX FAQ, documents, archives, etc. MacInTouch -- current Macintosh information, from vendor & others Shareware sites The Free On-line Dictionary of Computing PDS: The Performance Database Server of Computer Benchmark Return to Top Return to Top Newsgroups, USEnet, and Mailing Lists Usenet (Internet News Groups) Mailing list software & information Return to Top Return to Top

334

Synchronization in complex networks  

SciTech Connect (OSTI)

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.

Arenas, A.; Diaz-Guilera, A.; Moreno, Y.; Zhou, C.; Kurths, J.

2007-12-12T23:59:59.000Z

335

Sensor network algorithms and applications  

Science Journals Connector (OSTI)

...range-based localization methods for wireless sensor networks. They review...compression techniques for wireless sensor networks. They pay...consuming hundreds of megawatts of electricity. Careful monitoring of large...of the state of the art in wireless sensor networks. The articles...

2012-01-01T23:59:59.000Z

336

Network Operating Systems Partha Dasgupta  

E-Print Network [OSTI]

Network Operating Systems Partha Dasgupta Department of Computer Science and Engineering Arizona of Electrical Engineering] 1. Introduction Network Operating Systems extend the facilities and services provided by computer operating systems to support a set of computers, connected by a network. The environment managed

Dasgupta, Partha

337

Elizabeth Bautista  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Elizabeth Bautista Elizabeth Bautista Elizabeth Bautista ejb-headshot.jpg Elizabeth J. Bautista Group Lead, Operations Technology Group, EJBautista@lbl.gov Phone: (510) 486-7454 , Fax: (510) 486-4316 1 Cyclotron Road Mail Stop 943R0256 Berkeley, CA 94720 Biographical Sketch Elizabeth Bautista is Group Lead for the Operations Technology Group, the team who are the first line support of NERSC and ESnet (Energy Sciences Network www.es.net). Since joining NERSC in 1999, she has worked in the Computer Operations & Network Support Group, Workstation Support as a team lead and most recently in the Computational Systems Group as a member of the PDSF team. Being familiar with both operations and system administration, she brings a unique perspective as the lead and in continuing the tradition of support for both NERSC and ESnet. She

338

Partnerships  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Partnerships Partnerships R&D Overview 100G Testbed Virtual Circuits (OSCARS) Performance (perfSONAR) Tools Development Green Networking Authentication & Trust Federation (ATF) Partnerships Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Partnerships ESnet engages in active international collaborations with partners from the Research and Education (R&E) community as well as industry. This exchange of ideas provides the necessary input to develop advanced software and services targeted towards the express needs of scientists and technical community that supports them. Our collaborations focus on operational

339

Data Transfer Nodes Yield Results!  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

DTN DTN Data Transfer Nodes Yield Results August 1, 2011 | Tags: Accelerator Science, Data Transfer, ESnet Linda Vu, +1 510 495 2402, lvu@lbl.gov The ability to reliably move and share data around the globe is essential to scientific collaboration, that's why three Department of Energy (DOE) Scientific Computing Centers-Argonne and Oak Ridge Leadership Computing Facilities, and the National Energy Research Scientific Computing Center (NERSC)-have teamed up to focus on optimizing wide area network (WAN) transfers. This ongoing effort began several years ago when each site deployed dedicated transfer nodes (DTNs), optimized for carrying data between the DOE facilities. Today, engineers from each site continue to meet regularly with DOE's Energy Sciences Network staff (ESnet) to develop strategies

340

Current Testbed Research  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Research Research R&D Overview 100G Testbed Testbed Description Testbed Results Current Testbed Research Previous Testbed Research Proposal Process Terms and Conditions Virtual Circuits (OSCARS) Performance (perfSONAR) Tools Development Green Networking Authentication & Trust Federation (ATF) Partnerships Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US) 1 800-333-7638 (Inside the US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Current Testbed Research The following projects are currently using the ESnet Testbed. Previous testbed projects descriptions are located here. New Projects, Summer 2013 Project Name/PI End-system affinities and the performance of high-speed flows, Dipak Ghosal (UC Davis)

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

OSCARS.wsdl - OSCARS Service definition  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

wsdl - OSCARS Service definition wsdl - OSCARS Service definition Services Overview ECS Audio/Video Conferencing Fasterdata IPv6 Network Network Performance Tools (perfSONAR) ESnet OID Registry PGP Key Service Virtual Circuits (OSCARS) OSCARS Case Study Documentation User Manual FAQ Design Specifications Functional Specifications Notifications Publications Authorization Policy Default Attributes Message Security Clients For Developers Interfaces Server api Client api WSDL files OSCARS.wsdl - OSCARS Service definition OSCARS.xsd - Types used in service messages OSCARS-Notify.wsdl - OSCARS Notify Broker service defintion nmtopo-ctrlp.xsd - Types used for path specification and topology exchange Links Hardware Requirements DOE Grids Service Transition Contact Us Technical Assistance: 1 800-33-ESnet (Inside the US)

342

DOE/BES Workshop on Clean and Efficient Combustion of 21st Century Transportation Fuels  

Broader source: Energy.gov [DOE]

Presentation given at the 2007 Diesel Engine-Efficiency & Emissions Research Conference (DEER 2007). 13-16 August, 2007, Detroit, Michigan. Sponsored by the U.S. Department of Energy's (DOE) Office of FreedomCAR and Vehicle Technologies (OFCVT).

343

Third DOE BES Separations Research Workshop | U.S. DOE Office...  

Office of Science (SC) Website

Separations & Analysis Prog. Dr. Charles H Byers cbyers@isopro.net Chem Tech Division Oak Ridge National Laboratory Dr. Hank Cochran hdc@ornl.gov Chem Tech Division Oak Ridge...

344

Report on Hydrogen Storage Panel Findings in DOE-BES Sponsored...  

Broader source: Energy.gov (indexed) [DOE]

(Univ. Pittsburgh) Theory and Computation Thomas Klassen (GKSS- Research Center, Germany) Nanostuctured Hydrides Peter Eklund (Penn State Univ) Carbon related materials Basic...

345

DOE/BES/NSET annual report on growth of metal and semiconductor nanostructures using localized photocatalysts.  

SciTech Connect (OSTI)

Our overall goal is to understand and develop a novel light-driven approach to the controlled growth of unique metal and semiconductor nanostructures and nanomaterials. In this photochemical process, bio-inspired porphyrin-based photocatalysts reduce metal salts in aqueous solutions at ambient temperatures to provide metal nucleation and growth centers. Photocatalyst molecules are pre-positioned at the nanoscale to control the location and morphology of the metal nanostructures grown. Self-assembly, chemical confinement, and molecular templating are some of the methods used for nanoscale positioning of the photocatalyst molecules. When exposed to light, the photocatalyst molecule repeatedly reduces metal ions from solution, leading to deposition and the synthesis of the new nanostructures and nanostructured materials. Studies of the photocatalytic growth process and the resulting nanostructures address a number of fundamental biological, chemical, and environmental issues and draw on the combined nanoscience characterization and multi-scale simulation capabilities of the new DOE Center for Integrated Nanotechnologies, the University of New Mexico, and Sandia National Laboratories. Our main goals are to elucidate the processes involved in the photocatalytic growth of metal nanomaterials and provide the scientific basis for controlled synthesis. The nanomaterials resulting from these studies have applications in nanoelectronics, photonics, sensors, catalysis, and micromechanical systems. The proposed nanoscience concentrates on three thematic research areas: (1) the creation of nanoscale structures for realizing novel phenomena and quantum control, (2) understanding nanoscale processes in the environment, and (3) the development and use of multi-scale, multi-phenomena theory and simulation. Our goals for FY03 have been to understand the role of photocatalysis in the synthesis of dendritic platinum nanostructures grown from aqueous surfactant solutions under ambient conditions. The research is expected to lead to highly nanoengineered materials for catalysis mediated by platinum, palladium, and potentially other catalytically important metals. The nanostructures made also have potential applications in nanoelectronics, nanophotonics, and nanomagnetic systems. We also expect to develop a fundamental understanding of the uses and limitations of biomimetic photocatalysis as a means of producing metal and semiconductor nanostructures and nanomaterials. The work has already led to a relationship with InfraSUR LLC, a small business that is developing our photocatalytic metal reduction processes for environmental remediation. This work also contributes to science education at a predominantly Hispanic and Native American university.

Haddad, Raid Edward; Brinker, C. Jeffrey; Shelnutt, John Allen; Yang, Yi; Nuttall, H. Eric; Watt, Richard K.; Singl, Anup K.; Challa, Sivakumar R.; Wang, Zhongchun; van Swol, Frank B.; Pereira, Eulalia; Qiu, Yan; Jiang, Ying-Bing; Xu, Huifang; Medforth, Craig J.; Song, Yujiang

2003-10-01T23:59:59.000Z

346

DOE/BES Workshop on Clean and Efficient Combustion of 21st Century...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

DOEBES Workshop on Clean and Efficient Combustion of 21st Century Transportation Fuels DOEBES Workshop on Clean and Efficient Combustion of 21st Century Transportation Fuels...

347

Archives of BES CRAs April 2010 | U.S. DOE Office of Science...  

Office of Science (SC) Website

Effects .pdf file (26KB) Neutron and X-Ray Scattering X-Ray Scattering .pdf file (27KB) Neutron Scattering .pdf file (26KB) Electron and Scanning Probe Microscopies .pdf file...

348

NERSC/DOE BES Requirements Workshop Worksheet - Lin-Wang Wang  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

systems in energy applications. We like to understand the band alignment in a heterojunction nanostructure, the carrier dynamics and electron-phonon interaction in such a...

349

NERSC/DOE BES Requirements Workshop Worksheet - Hai-Ping Cheng  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

nano-wires, as well as magnetic materials and ntunneling junctions using high accuracy electronic structure calculations, large scale MD methods, and Green function techniques...

350

Benefits of BES | U.S. DOE Office of Science (SC)  

Office of Science (SC) Website

that improve the efficiency, economy, environmental acceptability, and safety of energy generation, conversion, transmission, storage, and use. For example, advances in...

351

Seventh BES (Basic Energy Sciences) catalysis and surface chemistry research conference  

SciTech Connect (OSTI)

Research programs on catalysis and surface chemistry are presented. A total of fifty-seven topics are included. Areas of research include heterogeneous catalysis; catalysis in hydrogenation, desulfurization, gasification, and redox reactions; studies of surface properties and surface active sites; catalyst supports; chemical activation, deactivation; selectivity, chemical preparation; molecular structure studies; sorption and dissociation. Individual projects are processed separately for the data bases. (CBS)

Not Available

1990-03-01T23:59:59.000Z

352

E-Print Network 3.0 - agency national network Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Network Implementation Plan... Consulting, Ltd. for assistance in development of this document. 12;National Network Implementation Plan... .1 Tracking Network National Portal...

353

Teacher Resource Center: Teacher Networks  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Teacher Networks Teacher Networks TRC Home TRC Fact Sheet Library Curricular Resources Science Fair Resources Bibliographies sciencelines The Best of sciencelines Archives Annotated List of URLs Catalog Teacher's Lounge Full Workshop Catalog Customized Workshops Scheduled Workshops Special Opportunities Teacher Networks Science Lab Fermilab Science Materials Samplers Order Form Science Safety Issues Tech Room Fermilab Web Resources Fermilab offers support to area networks where teachers share successful teaching materials and strategies. These groups meet monthly or bimonthly during the school year in local schools or colleges in order to share skills, teaching strategies and materials. Patterned after the Illinois State Physics Project, most of these networks are spin-offs of Fermilab's

354

Advanced Network Toolkit for Assessments  

Broader source: Energy.gov (indexed) [DOE]

Network Toolkit for Assessments Network Toolkit for Assessments and Remote Mapping (ANTFARM) Uses existing information to passively map control systems networks and identify cyber security perimeters Control systems operators require a map of their energy control system network in order to identify its electronic security perimeter, critical to meeting the North American Electric Reliability Corporation's (NERC) Critical Infrastructure Protection (CIP) standards. However, purchasing active, online scanning tools specifically for network mapping can be costly, and these tools can disrupt control system function, causing system latency and possibly affecting power supply. The ANTFARM software tool enables system operators to remotely and

355

Rule generation from neural networks  

SciTech Connect (OSTI)

The neural network approach has proven useful for the development of artificial intelligence systems. However, a disadvantage with this approach is that the knowledge embedded in the neural network is opaque. In this paper, we show how to interpret neural network knowledge in symbolic form. We lay down required definitions for this treatment, formulate the interpretation algorithm, and formally verify its soundness. The main result is a formalized relationship between a neural network and a rule-based system. In addition, it has been demonstrated that the neural network generates rules of better performance than the decision tree approach in noisy conditions. 7 refs.

Fu, L. [Univ. of Florida, Gainesville, FL (United States)

1994-08-01T23:59:59.000Z

356

Technical Information Network  

Broader source: Energy.gov [DOE]

DOE's Technical Information Network for Solid-State Lighting (TINSSL) increases awareness of SSL technology, performance, and appropriate applications. TINSSL members include representatives from regional energy efficiency organizations and program sponsors, utilities, state and local energy offices, lighting trade groups, and other stakeholders.

357

EBONEEUROPEAN BIODIVERSITY OBSERVATION NETWORK  

E-Print Network [OSTI]

EBONEEUROPEAN BIODIVERSITY OBSERVATION NETWORK Geert De Blust, Guy Laurijssens, Hans Van Calster of biodiversity monitoring through close collaboration of users and data providers #12;#12;Design of a monitoring-effectiveness Optimization of biodiversity monitoring through close collaboration of users and data providers Geert De Blust1

358

Lattice Gauge Tensor Networks  

E-Print Network [OSTI]

We present a unified framework to describe lattice gauge theories by means of tensor networks: this framework is efficient as it exploits the high amount of local symmetry content native of these systems describing only the gauge invariant subspace. Compared to a standard tensor network description, the gauge invariant one allows to speed-up real and imaginary time evolution of a factor that is up to the square of the dimension of the link variable. The gauge invariant tensor network description is based on the quantum link formulation, a compact and intuitive formulation for gauge theories on the lattice, and it is alternative to and can be combined with the global symmetric tensor network description. We present some paradigmatic examples that show how this architecture might be used to describe the physics of condensed matter and high-energy physics systems. Finally, we present a cellular automata analysis which estimates the gauge invariant Hilbert space dimension as a function of the number of lattice sites and that might guide the search for effective simplified models of complex theories.

Pietro Silvi; Enrique Rico; Tommaso Calarco; Simone Montangero

2014-10-12T23:59:59.000Z

359

Network Economics Anna Nagurney  

E-Print Network [OSTI]

and Operations Management Isenberg School of Management University of Massachusetts Amherst, Massachusetts 01003 Handbook of Computational Econometrics David Belsley and Erricos Kontoghiorghes, Editors, John Wiley & Sons, network theory has developed into a powerful and dynamic mechanism for abstracting complex problems, which

Nagurney, Anna

360

Financial Networks Anna Nagurney  

E-Print Network [OSTI]

of Management University of Massachusetts Amherst, Massachusetts 01003 MEASURING SYSTEMIC RISK Conference and realizing a timely response to evolving events. Anna Nagurney Financial Networks #12;Characteristics by the intersection of supply and demand curves in the context of spatially separate markets in which transportation

Nagurney, Anna

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Microsystem process networks  

DOE Patents [OSTI]

Various aspects and applications of microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having exergetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

Wegeng, Robert S. (Richland, WA); TeGrotenhuis, Ward E. (Kennewick, WA); Whyatt, Greg A. (West Richland, WA)

2006-10-24T23:59:59.000Z

362

Transactional Network Platform: Applications  

SciTech Connect (OSTI)

In FY13, Pacific Northwest National Laboratory (PNNL) with funding from the Department of Energys (DOEs) Building Technologies Office (BTO) designed, prototyped and tested a transactional network platform to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). Initially, in FY13, the concept demonstrated transactions between packaged rooftop air conditioners and heat pump units (RTUs) and the electric grid using applications or "agents" that reside on the platform, on the equipment, on a local building controller or in the Cloud. The transactional network project is a multi-lab effort with Oakridge National Laboratory (ORNL) and Lawrence Berkeley National Laboratory (LBNL) also contributing to the effort. PNNL coordinated the project and also was responsible for the development of the transactional network (TN) platform and three different applications associated with RTUs. This document describes two applications or "agents" in details, and also summarizes the platform. The TN platform details are described in another companion document.

Katipamula, Srinivas; Lutes, Robert G.; Ngo, Hung; Underhill, Ronald M.

2013-10-31T23:59:59.000Z

363

Network on metachip architectures  

Science Journals Connector (OSTI)

The size of systems on a chip is limited by our ability to design and fabricate such systems, staying within the appropriate costs depending on the application. In this paper, we propose a divide-and-conquer approach, Quilt Packaging, to be utilized ... Keywords: network-on-chip, quilt packaging, system-on-chip

Ismo Hnninen; Wayne Buckhanan; Michael Niemier; Gary H. Bernstein

2012-12-01T23:59:59.000Z

364

Lattice Gauge Tensor Networks  

E-Print Network [OSTI]

We present a unified framework to describe lattice gauge theories by means of tensor networks: this framework is efficient as it exploits the high amount of local symmetry content native of these systems describing only the gauge invariant subspace. Compared to a standard tensor network description, the gauge invariant one allows to speed-up real and imaginary time evolution of a factor that is up to the square of the dimension of the link variable. The gauge invariant tensor network description is based on the quantum link formulation, a compact and intuitive formulation for gauge theories on the lattice, and it is alternative and can be combined with the global symmetric tensor network description. We present some paradigmatic examples that show how this architecture might be used to describe the physics of condensed matter and high-energy physics systems. Finally, we present a cellular automata analysis which estimates the gauge invariant Hilbert space dimension as a function of the number of lattice sites...

Silvi, Pietro; Calarco, Tommaso; Montangero, Simone

2014-01-01T23:59:59.000Z

365

Microsystem process networks  

DOE Patents [OSTI]

Various aspects and applications or microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

Wegeng, Robert S [Richland, WA; TeGrotenhuis, Ward E [Kennewick, WA; Whyatt, Greg A [West Richland, WA

2010-01-26T23:59:59.000Z

366

Microsystem process networks  

DOE Patents [OSTI]

Various aspects and applications of microsystem process networks are described. The design of many types of Microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

Wegeng, Robert S. (Richland, WA); TeGrotenhuis, Ward E. (Kennewick, WA); Whyatt, Greg A. (West Richland, WA)

2007-09-18T23:59:59.000Z

367

Directory Enabled Policy Based Networking  

SciTech Connect (OSTI)

This report presents a discussion of directory-enabled policy-based networking with an emphasis on its role as the foundation for securely scalable enterprise networks. A directory service provides the object-oriented logical environment for interactive cyber-policy implementation. Cyber-policy implementation includes security, network management, operational process and quality of service policies. The leading network-technology vendors have invested in these technologies for secure universal connectivity that transverses Internet, extranet and intranet boundaries. Industry standards are established that provide the fundamental guidelines for directory deployment scalable to global networks. The integration of policy-based networking with directory-service technologies provides for intelligent management of the enterprise network environment as an end-to-end system of related clients, services and resources. This architecture allows logical policies to protect data, manage security and provision critical network services permitting a proactive defense-in-depth cyber-security posture. Enterprise networking imposes the consideration of supporting multiple computing platforms, sites and business-operation models. An industry-standards based approach combined with principled systems engineering in the deployment of these technologies allows these issues to be successfully addressed. This discussion is focused on a directory-based policy architecture for the heterogeneous enterprise network-computing environment and does not propose specific vendor solutions. This document is written to present practical design methodology and provide an understanding of the risks, complexities and most important, the benefits of directory-enabled policy-based networking.

KELIIAA, CURTIS M.

2001-10-01T23:59:59.000Z

368

Renormalization flows in complex networks  

Science Journals Connector (OSTI)

Complex networks have acquired a great popularity in recent years, since the graph representation of many natural, social, and technological systems is often very helpful to characterize and model their phenomenology. Additionally, the mathematical tools of statistical physics have proven to be particularly suitable for studying and understanding complex networks. Nevertheless, an important obstacle to this theoretical approach is still represented by the difficulties to draw parallelisms between network science and more traditional aspects of statistical physics. In this paper, we explore the relation between complex networks and a well known topic of statistical physics: renormalization. A general method to analyze renormalization flows of complex networks is introduced. The method can be applied to study any suitable renormalization transformation. Finite-size scaling can be performed on computer-generated networks in order to classify them in universality classes. We also present applications of the method on real networks.

Filippo Radicchi; Alain Barrat; Santo Fortunato; Jos J. Ramasco

2009-02-06T23:59:59.000Z

369

Power Control and Transmission Scheduling for Network Utility Maximization in Wireless Networks  

E-Print Network [OSTI]

Power Control and Transmission Scheduling for Network Utility Maximization in Wireless Networks Min power control and transmis- sion scheduling problem in wireless networks with average power constraints. Index Terms--Network utility maximization, power control, transmission scheduling, column generation I

Sharma, Vinod

370

Mobile Computing/Mobile Computing/Mobile Computing/Mobile Computing/ Mobile NetworksMobile NetworksMobile NetworksMobile Networks  

E-Print Network [OSTI]

Mobile Computing/Mobile Computing/Mobile Computing/Mobile Computing/ Mobile NetworksMobile NetworksMobile NetworksMobile Networks Mobile IP Prof. Chansu Yu 2 Contents IP for Wired Network Mobile IP Overview Basic Mobile IP Agent Discovery Registration Tunneling Route Optimization Current Topics #12;3 Simplified

Yu, Chansu

371

Securing Ad Hoc Networks Lidong Zhou  

E-Print Network [OSTI]

Securing Ad Hoc Networks Lidong Zhou Department of Computer Science Zygmunt J. Haas School of Electrical Engineering Cornell University Ithaca, NY 14853 Abstract Ad hoc networks are a new wireless networking paradigm for mobile hosts. Unlike traditional mobile wireless networks, ad hoc networks do

Schneider, Fred B.

372

Transportation Networks and Location A Geometric Approach  

E-Print Network [OSTI]

Transportation Networks and Location A Geometric Approach Belén Palop1,2 1Departamento de March 2009 Florida State University #12;Belén Palop, UVa, SUNY Outline Transportation Network Model;Transportation Network Model Belén Palop, UVa, SUNY Outline Transportation Network Model Network placement

Palop del Río, Belén

373

Multiple crossbar network: A switched high-speed local network  

SciTech Connect (OSTI)

The Multiple Crossbar Network (MCN) is a prototype High-Speed Local Network at the Los Alamos National Laboratory. It will interconnect supercomputers, network servers and workstations from various commercial vendors. The MCN can also serve as a backbone for message traffic between local area networks. The MCN is a switched local network of switching nodes called Cross-Point Stars (CPs). Hosts and CPs are connected by 800-Mbit/s (100-Mbyte/s) point-to-point ANSI High-Speed Channels. CPs include RISC-based network protocol processors called Crossbar Interfaces and a switching core called the Crossbar Switch. Protocols include physical, data link, intranet, and network access functionality. Various internet and transport protocols are intended to run above the MCN protocol suite. A network management and simple naming service is also included within the Los Alamos Network Architecture. Immediate applications include visualization. The MCN is intended to also serve as a framework for multicomputer applications. 36 refs., 10 figs.

Hoebelheinrich, R.; Thomsen, R.

1989-01-01T23:59:59.000Z

374

Microsoft Word - Motivation, Design, Deployment and Evolution of OSCARS - Johnston.v1.4.docx  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

TERENA Networking Conference TERENA Networking Conference 16 - 19 May, 2011 Prague, Czech Republic Motivation, Design, Deployment and Evolution of a Guaranteed Bandwidth Network Service William E. Johnston, Chin Guok, Evangelos Chaniotakis ESnet and Lawrence Berkeley National Laboratory, Berkeley California, U.S.A Paper type Technical paper Abstract Much of modern science is dependent on high performance distributed computing and data handling. This distributed infrastructure, in turn, depends on high speed networks and services - especially when the science infrastructure is widely distributed geographically - to enable the science because the science is dependent on high throughput so that the distributed computing and data management systems will be able to analyze data as

375

Cost evaluations of the protected network layer packet redundancy scheme  

Science Journals Connector (OSTI)

Feature Issue on High Availability in Optical Networks The protected network layer packet redundancy scheme...

verby, H

2006-01-01T23:59:59.000Z

376

A hybrid network architecture for modular data centers  

E-Print Network [OSTI]

include networking, power and cooling equip- ment besidesgeared with networking, power and cooling equipment. At the

Radhakrishnan, Sivasankar

2010-01-01T23:59:59.000Z

377

Decentring Policy Networks: Lessons and Prospects  

E-Print Network [OSTI]

of policy networks lacked a suitable micro-theory. As weexplains network behaviour as a product of the micro-levelof networks. Thus the decentred approach offers a micro-

Bevir, Mark

2009-01-01T23:59:59.000Z

378

Decentring Policy Networks: A Theoretical Agenda  

E-Print Network [OSTI]

In their view, at the micro-level, networks are comprised ofbetween the micro- (or individual), meso- (or network), andpolicy networks as a meso-level concept. It links the micro-

Bevir, Mark

2009-01-01T23:59:59.000Z

379

Evolution and statistics of biological regulatory networks  

E-Print Network [OSTI]

In this thesis, I study the process of evolution of the gene regulatory network in Escherichia coli. First, I characterize the portion of the network that has been documented, and then I simulate growth of the network. In ...

Chandalia, Juhi Kiran, 1979-

2005-01-01T23:59:59.000Z

380

A VALIDATION INDEX FOR ARTIFICIAL NEURAL NETWORKS  

E-Print Network [OSTI]

A VALIDATION INDEX FOR ARTIFICIAL NEURAL NETWORKS Stephen Roberts, Lionel Tarassenko, James Pardey and estimation properties of artificial neural networks. Like many `traditional' statistical techniques & David Siegwart Neural Network Research Group Department of Engineering Science University of Oxford, UK

Roberts, Stephen

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Community structure in the phonological network  

E-Print Network [OSTI]

Community structure, which refers to the presence of densely connected groups within a larger network, is a common feature of several real-world networks from a variety of domains such as the human brain, social networks ...

Siew, Cynthia S. Q.

2013-08-27T23:59:59.000Z

382

Hybrid Routing in Delay Tolerant Networks.  

E-Print Network [OSTI]

??This work addresses the integration of today's infrastructure-based networks with infrastructure-less networks. The resulting Hybrid Routing System allows for communication over both network types and (more)

Mayer, Christoph P.

2012-01-01T23:59:59.000Z

383

Hybrid routing in delay tolerant networks.  

E-Print Network [OSTI]

??This work addresses the integration of today\\'s infrastructure-based networks with infrastructure-less networks. The resulting Hybrid Routing System allows for communication over both network types and (more)

Mayer, Christoph P.

2012-01-01T23:59:59.000Z

384

Using Recurrent Networks for Dimensionality Reduction  

E-Print Network [OSTI]

This report explores how recurrent neural networks can be exploited for learning high-dimensional mappings. Since recurrent networks are as powerful as Turing machines, an interesting question is how recurrent networks ...

Jones, Michael J.

1992-09-01T23:59:59.000Z

385

Utilizing Solar Power in Wireless Sensor Networks  

Science Journals Connector (OSTI)

Sensor networks are designed especially for deploymentin adverse and non-accessible areas without a fixed infrastructure.Therefore, energy conservation plays a crucialrole for these networks. We propose to utilize solar powerin wireless sensor networks, ...

Thiemo Voigt; Hartmut Ritter; Jochen Schiller

2003-10-01T23:59:59.000Z

386

Scale-free information systems networks  

E-Print Network [OSTI]

Many real, complex networks have been shown to be scale-free. Scale-free in networks mean that their degree distribution is independent of the network size, have short path lengths and are highly clustered. We identify the ...

Ang, Wee Horng

2006-01-01T23:59:59.000Z

387

Transactional Network | Department of Energy  

Energy Savers [EERE]

first demonstrated the transactional concept with networked rooftop air conditioners and heat pumps, and it is now extending the concept to lighting and refrigeration systems....

388

Helper's Network Gazette August 1994  

E-Print Network [OSTI]

Helpers Network Gazette - August 1994 file:///K|/...t/Helper's%20Gazette%20Newsletter/Beauty%20and%20the%20Beast%20Helper's%20Gazette%201994-08%20(August)%20.htm[3/31/2013 5:37:11 PM] The Helpers' Network GAZETTE - August 1994 a monthly newsletter...-i-ana, Nan can make copies. Any of these videos available for $8.50 from Helpers' Network. Helpers Network Gazette - August 1994 file:///K|/...t/Helper's%20Gazette%20Newsletter/Beauty%20and%20the%20Beast%20Helper's%20Gazette%201994-08%20(August)%20.htm[3...

1994-01-01T23:59:59.000Z

389

Communication in Home Area Networks  

E-Print Network [OSTI]

line from the generator to substation while MV isdistribution network between substation and user end. A LVa number of routers/substations and thousands of sensor

Wang, Yubo

2012-01-01T23:59:59.000Z

390

Fusion Energy Sciences Network Requirements  

E-Print Network [OSTI]

Division, and the Office of Fusion Energy Sciences. This isFusion Energy Sciences NetworkRequirements Office of Fusion Energy Sciences Energy

Dart, Eli

2014-01-01T23:59:59.000Z

391

Power network analysis and optimization  

E-Print Network [OSTI]

hierarchical power distribution design with a power tree [T. Roy, Power distribution system design methodology andChen, 3D Power Distribution Network Co-design for Nanascale

Zhang, Wanping

2009-01-01T23:59:59.000Z

392

Policies for implementing network firewalls  

SciTech Connect (OSTI)

Corporate networks are frequently protected by {open_quotes}firewalls{close_quotes} or gateway systems that control access to/from other networks, e.g., the Internet, in order to reduce the network`s vulnerability to hackers and other unauthorized access. Firewalls typically limit access to particular network nodes and application protocols, and they often perform special authentication and authorization functions. One of the difficult issues associated with network firewalls is determining which applications should be permitted through the firewall. For example, many networks permit the exchange of electronic mail with the outside but do not permit file access to be initiated by outside users, as this might allow outside users to access sensitive data or to surreptitiously modify data or programs (e.g., to intall Trojan Horse software). However, if access through firewalls is severely restricted, legitimate network users may find it difficult or impossible to collaborate with outside users and to share data. Some of the most serious issues regarding firewalls involve setting policies for firewalls with the goal of achieving an acceptable balance between the need for greater functionality and the associated risks. Two common firewall implementation techniques, screening routers and application gateways, are discussed below, followed by some common policies implemented by network firewalls.

Brown, C.D.

1994-05-01T23:59:59.000Z

393

Power network analysis and optimization  

E-Print Network [OSTI]

Marek-Sadowska, On-chip power supply network optimizationtechniques for full-chip power supply noise analysis IEEEFull-chip vectorless dynamic power integrity analysis and

Zhang, Wanping

2009-01-01T23:59:59.000Z

394

Imprinted Networks as Chiral Pumps  

E-Print Network [OSTI]

We investigate the interaction between a chirally imprinted network and a solvent of chiral molecules. We find, a liquid crystalline polymer network is preferentially swollen by one component of a racemic solvent. This ability to separate is linked to the chiral order parameter of the network, and can be reversibly controlled via temperature or a mechanical deformation. It is maximal near the point at which the network loses its imprinted structure. One possible practical application of this effect would be a mechanical device for sorting mixed chiral molecules.

Y. Mao; M. Warner

2001-01-12T23:59:59.000Z

395

Engaging Edge Networks in Preventing and Mitigating Undesirable Network Traffic  

E-Print Network [OSTI]

Introduction The current Internet has few effective mechanisms to prevent a user from flooding network traffic available to well-behaved users, thus pos- ing a significant threat to the Internet's viability (see IAB. In our view, edge networks are in the best position to control hosts who abuse the trust because

Wang, Lan

396

Networked Graphics: Building Networked Games and Virtual Environments  

Science Journals Connector (OSTI)

This broad-ranging book equips programmers and designers with a thorough grounding in the techniques used to create truly network-enabled computer graphics and games. Written for graphics/game/VE developers and students, it assumes no prior knowledge ... Keywords: Computer Animation, Computer Graphics, Computer Science, Computers, Game Programming, Interactive & Multimedia, Networking, Video & Electronic, Virtual Reality

Anthony Steed; Manuel Fradinho Oliveira

2009-11-01T23:59:59.000Z

397

Deadline-aware Broadcasting in Wireless Networks with Network Coding  

E-Print Network [OSTI]

on time. Index Terms--Broadcasting, broadcast tree, network coding, energy efficiency, deadline, NP 19122 Department of Electrical & Computer Engineering, New Jersey Institute of Technology, Newark, NJ of transmissions, which improves the energy efficiency of wireless networks. On the other hand, delaying

Wu, Jie

398

Ecological NetworksEcological Networks 15 September 2009  

E-Print Network [OSTI]

Antagonistic networks ­ Food webs Host parasite/parasitoid webs­ Hostparasite/parasitoid webs · Mutualistic networks ­ Plantseed disperser webs ­ Plantpollinator webs ­ Plantant webs Ings et al 2009 J Animal Ecol #12;Food websFood webs · Directed links denoteDirected links denote direction of energy flow http

Albert, Réka

399

NERSC's Data Transfer Nodes  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Data Transfer Nodes Data Transfer Nodes Data Transfer Nodes Overview The data transfer nodes are NERSC servers dedicated to performing transfers between NERSC data storage resources such as HPSS and the NERSC Global Filesystem (NGF), and storage resources at other sites including the Leadership Computing Facility at ORNL (Oak Ridge National Laboratory). These nodes are being managed (and monitored for performance) as part of a collaborative effort between ESnet, NERSC, and ORNL to enable high performance data movement over the high-bandwidth 10Gb ESnet wide-area network (WAN). Restrictions In order to keep the data transfer nodes performing optimally for data transfers, we request that users restrict interactive use of these systems to tasks that are related to preparing data for transfer or are directly

400

Fact Sheet: Better Buildings Residential Network  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

bbrn What Is the Residential Network? The Better Buildings Residential Network connects energy efficiency programs and partners to share best practices and learn from one another...

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Data and Networking | Argonne Leadership Computing Facility  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Networking Data and Networking Data Storage The ALCF's data storage system is used to retain the data generated by simulations and visualizations. Disk storage provides...

402

In Home Networking using Optical Fiber  

Science Journals Connector (OSTI)

Increased bandwidth requirements for in-home networks create opportunities for optical fiber interconnects. We outline the requirements for in-home networking and discuss the...

Ten, Sergey

403

Home Network Technologies and Automating Demand Response  

E-Print Network [OSTI]

potential role of home automation networks in implementinghow existing and future home automation systems may providehome networks" and "home automation" are frequently used

McParland, Charles

2010-01-01T23:59:59.000Z

404

Better Buildings Residential Network | Department of Energy  

Energy Savers [EERE]

more. Residential Network Members Welcome Our Newest Members Cascadia Consulting Group Johnson Environmental The Building Performance Center, Inc. *Residential Network members that...

405

Local Policy Networks and Agricultural Watershed Management  

E-Print Network [OSTI]

Local Policy Networks and Agricultural Watershed Management Mark Lubell University of California of networks in promoting cooperation (Bosch, Cook, and Fuglie 1995; Lubell et al. 2002; Marshall 2005

Lubell, Mark

406

Southeast Energy Efficiency Alliance Launches Finance Network...  

Broader source: Energy.gov (indexed) [DOE]

Southeast Energy Efficiency Alliance Launches Finance Network Southeast Energy Efficiency Alliance Launches Finance Network Photo of two hands holding dollar bills shaped like a...

407

Better Buildings Residential Network Orientation Peer Exchange...  

Broader source: Energy.gov (indexed) [DOE]

Better Buildings Residential Network Orientation Peer Exchange Webinar Better Buildings Residential Network Orientation Peer Exchange Webinar September 11, 2014 7:00PM to 8:3...

408

Placement of network services in a sensor network  

Science Journals Connector (OSTI)

An important challenge in designing a wireless sensor network is to maximise the network's lifetime. In a hierarchical cluster-based network, a key design issue is the placement of cluster heads (data loggers) such that the total power consumed by the overall network is minimised. Another key design goal is the localisation of sensors. In this study, we consider the placement of beacons and data loggers in the Cosumnes River Preserve. We consider a hybrid network in which the wireless sensors are deployed randomly into an irregular terrain while the data loggers and beacons are placed in a planned manner to satisfy the following three objectives: provide complete area coverage; load balance each cluster; minimise the total power consumption for collecting the data. We formulated an optimisation problem to determine the location of data loggers and beacons ?? which is solved using an Integer Linear Program (ILP).

Jennifer Yick; Gregory Pasternack; Biswanath Mukherjee; Dipak Ghosal

2006-01-01T23:59:59.000Z

409

Network Bandwidth Utilization Forecast Model on High Bandwidth Network  

SciTech Connect (OSTI)

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

Yoo, Wucherl; Sim, Alex

2014-07-07T23:59:59.000Z

410

Nordic network for Sustainable Energy  

E-Print Network [OSTI]

Nordic network for Sustainable Energy Systems in Isolated Locations (NordSESIL) Gordon A. Mackenzie of the Nordic region to access sustainable energy solutions by creating and stimulating a network of relevant sustainable energy projects happening' in isolated areas of the Nordic region. #12;Partners, organisation (1

411

Networks in Finance Anna Nagurney  

E-Print Network [OSTI]

Chapter 1 Networks in Finance Anna Nagurney Department of Finance and Operations Management as Chapter 17 in the Handbook on IT and Finance, D. Seese, C. Weinhardt, and F. Schlottmann, Editors, Springer (2008), Berlin, Germany. Summary. This handbook chapter traces the history of networks in finance

Nagurney, Anna

412

Cooperation in Cognitive Radio Networks  

Science Journals Connector (OSTI)

The operation of cognitive radio (CR) networks involves opportunistic access to the spectrum licensed to primary users (PUs) by secondary users (SUs). Traditionally, this access is performed in such a way that the PUs suffer minimal interference to their ... Keywords: cognitive radio networks, cooperation, cooperative relays

Pedro Smith Coutinho, Jos Ferreira de Rezende, Valmir Carneiro Barbosa

2014-05-01T23:59:59.000Z

413

Network Fusion Pascal Fradet1  

E-Print Network [OSTI]

Network Fusion Pascal Fradet1 and St´ephane Hong Tuan Ha2 1 INRIA Rh^one-Alpes 655, av. de l composition method which strives to reconcile modularity and efficiency. Our technique, network fusion fusion. Fusion allows to replace internal commu- nications by assignments and alleviates most time

Paris-Sud XI, Université de

414

Sensors, Controls, & Transactional Network Reports  

Broader source: Energy.gov [DOE]

Reports from the sensors, controls, and transactional network program. The transactional network is between appliances, buildings, and utilities, and can enable Smart Buildings -- buildings with technologies and control systems that can not only optimize energy performance and comfort, but also support energy-related transactions outside the building envelope.

415

Geometric algorithms for sensor networks  

Science Journals Connector (OSTI)

...the communication cost and energy consumption by avoiding network-wide...network is a two-dimensional grid. The information storage curves...and X. Lin2001Loop-free hybrid single-path/flooding routing...D. Joseph2001Tapestry: an infrastructure for fault-tolerant wide-area...

2012-01-01T23:59:59.000Z

416

Bursty subgraphs in social networks  

Science Journals Connector (OSTI)

Data available through social media and content sharing platforms present opportunities for analysis and mining. In the context of social networks, it is interesting to formalize and locate bursts of activities amongst users, related to a particular ... Keywords: bursty subgraphs, information burst, social networks, twitter

Milad Eftekhar; Nick Koudas; Yashar Ganjali

2013-02-01T23:59:59.000Z

417

Costeffective Outbreak Detection in Networks  

E-Print Network [OSTI]

on how contaminants spread in the network Problem posed by US Environmental Protection Agency S On which nodes should we place sensors to efficiently detect the all possible contaminations? S #12 Given a graph G(V,E) and a budget B for sensors and data on how contaminations spread over the network

Yang, Qiang

418

RNEDE: Resilient Network Design Environment  

SciTech Connect (OSTI)

Modern living is more and more dependent on the intricate web of critical infrastructure systems. The failure or damage of such systems can cause huge disruptions. Traditional design of this web of critical infrastructure systems was based on the principles of functionality and reliability. However, it is increasingly being realized that such design objectives are not sufficient. Threats, disruptions and faults often compromise the network, taking away the benefits of an efficient and reliable design. Thus, traditional network design parameters must be combined with self-healing mechanisms to obtain a resilient design of the network. In this paper, we present RNEDEa resilient network design environment that that not only optimizes the network for performance but tolerates fluctuations in its structure that result from external threats and disruptions. The environment evaluates a set of remedial actions to bring a compromised network to an optimal level of functionality. The environment includes a visualizer that enables the network administrator to be aware of the current state of the network and the suggested remedial actions at all times.

Venkat Venkatasubramanian, Tanu Malik, Arun Giridh; Craig Rieger; Keith Daum; Miles McQueen

2010-08-01T23:59:59.000Z

419

Integrated global background monitoring network  

SciTech Connect (OSTI)

This paper describes the background and elucidates the need for an integrated global background monitoring network. This network should: establish reference levels for pollutants that have potential for global contaminatin, serve as an early warning site for detecting global spread of pollutants, and establish baseline levels for selected ecosystem parameters against which data from more impacted areas can be compared. This paper proposes the following: (1) establish an integrated global background monitoring network for pollutants and ecosystem parameters; (2) pollutant measurements be multi-media; (3) carry out ecosystem parameter studies in conjunction with pollutant measurements; (4) the network be maintained for an indefinite period of time; (5) the network be established using the international biosphere reserve system as the universe from which a subset of monitoring sites are drawn; and (6) that the project be under the overall direction of the Global Environmental Monitoring System. 43 references, 1 figure, 1 table.

Wiersma, G.B.

1984-08-01T23:59:59.000Z

420

Collective network for computer structures  

DOE Patents [OSTI]

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to the needs of a processing algorithm.

Blumrich, Matthias A; Coteus, Paul W; Chen, Dong; Gara, Alan; Giampapa, Mark E; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd E; Steinmacher-Burow, Burkhard D; Vranas, Pavlos M

2014-01-07T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Collective network for computer structures  

DOE Patents [OSTI]

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

Blumrich, Matthias A. (Ridgefield, CT); Coteus, Paul W. (Yorktown Heights, NY); Chen, Dong (Croton On Hudson, NY); Gara, Alan (Mount Kisco, NY); Giampapa, Mark E. (Irvington, NY); Heidelberger, Philip (Cortlandt Manor, NY); Hoenicke, Dirk (Ossining, NY); Takken, Todd E. (Brewster, NY); Steinmacher-Burow, Burkhard D. (Wernau, DE); Vranas, Pavlos M. (Bedford Hills, NY)

2011-08-16T23:59:59.000Z

422

Introduction to Ad hoc Networks CS-647: Advanced Topics in Wireless Networks  

E-Print Network [OSTI]

1-1 Introduction to Ad hoc Networks CS-647: Advanced Topics in Wireless Networks Drs. Baruch Awerbuch 2008 #12;1-2 Outline What is an ad hoc network? Challenges facing ad hoc networks History of Ad C. K. Toh, Chapter 3, "Ad Hoc Wireless Networks", Prentice Hall, 2002 D. P. Agrawal and Qing

Amir, Yair

423

Transportation Network Equilibrium --The Formalism for Networks Today from the Internet  

E-Print Network [OSTI]

Telecommunications Energy Supply Chains Interregional Trade Industrial Organization Location Theory Spatial #12;US Railroad Freight Flows #12;Natural Gas Pipeline Network in the US #12;World Oil Trading Network and Complex Networks · A New Network Performance/Efficiency Measure with Applications to Network Systems

Nagurney, Anna

424

In Vitro Synthetic Transcriptional Networks Jongmin Kim  

E-Print Network [OSTI]

, we engineered artificial tran- scriptional networks consisting of synthetic DNA switches, regulated

Winfree, Erik

425

Detecting Network Vulnerabilities Through Graph Theoretical Methods  

E-Print Network [OSTI]

benchmark power networks. 1 Introduction The electric power grid network is susceptible to power outages of our work is power networks, our techniques are applicable to other systems such as the transportation vulnerabilities in power networks is an important prob- lem, as even a small number of vulnerable connections can

Geddes, Cameron Guy Robinson

426

Artificial Neural Network Portion of Coil Study  

E-Print Network [OSTI]

Artificial Neural Network Portion of Coil Study LTC William M. Crocoll School of Systems TO ARTIFICIAL NEURAL NETWORKS A neural network is a massively parallel system comprised of many highly of the brain (Dayhoff, 1990). A major task for a neural network is to learn and maintain a model of the world

Putten, Peter van der

427

Semiring Artificial Neural Networks and Weighted Automata  

E-Print Network [OSTI]

Semiring Artificial Neural Networks and Weighted Automata And an Application to Digital Image neural networks and weighted automata. For this task, we introduce semiring artificial neural networks, that is, artificial neural networks which implement the addition and the multiplication of semirings. We

Hoelldobler, Steffen

428

Artificial Bee Colony Training of Neural Networks  

E-Print Network [OSTI]

Artificial Bee Colony Training of Neural Networks John A. Bullinaria and Khulood AlYahya School of artificial Neural Networks (NNs). Of course, there already exist many hybrid neural network learning for optimization, that has previously been applied successfully to the training of neural networks. This paper ex

Bullinaria, John

429

Introduction to Artificial Intelligence Neural Networks  

E-Print Network [OSTI]

Introduction to Artificial Intelligence (G51IAI) Dr Rong Qu Neural Networks #12;G51IAI ­ Introduction to AI Neural Networks Chapter 20 ­ Artificial Intelligence : A Modern Approach (AIMA) Russell ­ Introduction to AI Neural Networks More precisely: Artificial Neural Networks Simulating, on a computer, what

Qu, Rong

430

Energy Consumption Issues on Mobile Network Systems  

Science Journals Connector (OSTI)

This paper describes energy consumption demographic data in operating real mobile networks. We examine published data from NTT DoCoMo, which is the largest mobile telecommunication operator in Japan and operating nation-wide 3G networks, and identify ... Keywords: Moble Network, Power Consumption, Battery, CO2, Green Network

Minoru Etoh; Tomoyuki Ohya; Yuji Nakayama

2008-07-01T23:59:59.000Z

431

Introduction to Network Science 1 Random Models  

E-Print Network [OSTI]

Introduction to Network Science 1 Random Models #12;Introduction to Network Science 2 mean degree in a graph with exactly m edges Taylor series reminder: #12;Introduction to Network Science 3 In contrast to the degree distribution in random model ... #12;Introduction to Network Science 4 In contrast to the degree

Safro, Ilya

432

Slide #1CENTER FOR INTEGRATED ACCESS NETWORKS  

E-Print Network [OSTI]

Slide #1CENTER FOR INTEGRATED ACCESS NETWORKS Photonics Communication Engineering Khanh Kieu, Ph.D. College of Optical Sciences, University of Arizona #12;Slide #2CENTER FOR INTEGRATED ACCESS NETWORKS multiplexing · Network topology #12;Slide #3CENTER FOR INTEGRATED ACCESS NETWORKS Communication Source

Kieu, Khanh

433

Dynamic Networks: Recent Results and Applications  

E-Print Network [OSTI]

Networks provide us with the means to cross distance in order to conduct our work, and to see our. #12;Duke Energy Gas Pipeline Network #12;Components of Common Physical Networks Network System Nodes Links Flows Transportation Intersections, Homes, Workplaces, Airports, Railyards Roads, Airline Routes

Nagurney, Anna

434

Aging and functional brain networks  

SciTech Connect (OSTI)

Aging is associated with changes in human brain anatomy and function and cognitive decline. Recent studies suggest the aging decline of major functional connectivity hubs in the 'default-mode' network (DMN). Aging effects on other networks, however, are largely unknown. We hypothesized that aging would be associated with a decline of short- and long-range functional connectivity density (FCD) hubs in the DMN. To test this hypothesis, we evaluated resting-state data sets corresponding to 913 healthy subjects from a public magnetic resonance imaging database using functional connectivity density mapping (FCDM), a voxelwise and data-driven approach, together with parallel computing. Aging was associated with pronounced long-range FCD decreases in DMN and dorsal attention network (DAN) and with increases in somatosensory and subcortical networks. Aging effects in these networks were stronger for long-range than for short-range FCD and were also detected at the level of the main functional hubs. Females had higher short- and long-range FCD in DMN and lower FCD in the somatosensory network than males, but the gender by age interaction effects were not significant for any of the networks or hubs. These findings suggest that long-range connections may be more vulnerable to aging effects than short-range connections and that, in addition to the DMN, the DAN is also sensitive to aging effects, which could underlie the deterioration of attention processes that occurs with aging.

Tomasi D.; Tomasi, D.; Volkow, N.D.

2011-07-11T23:59:59.000Z

435

Information mobility in complex networks  

Science Journals Connector (OSTI)

The concept of information mobility in complex networks is introduced on the basis of a stochastic process taking place in the network. The transition matrix for this process represents the probability that the information arising at a given node is transferred to a target one. We use the fractional powers of this transition matrix to investigate the stochastic process at fractional time intervals. The mobility coefficient is then introduced on the basis of the trace of these fractional powers of the stochastic matrix. The fractional time at which a network diffuses 50% of the information contained in its nodes (1/k50) is also introduced. We then show that the scale-free random networks display a better spread of information than the non-scale-free ones. We study 38 real-world networks and analyze their performance in spreading information from their nodes. We find that some real-world networks perform even better than the scale-free networks with the same average degree and we point out some of the structural parameters that make this possible.

Ernesto Estrada

2009-08-05T23:59:59.000Z

436

Computer Networking Group | Stanford Synchrotron Radiation Lightsource  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Networking Group Networking Group Do you need help? For assistance please submit a CNG Help Request ticket. CNG Logo Chris Ramirez SSRL Computer and Networking Group Manager (650) 926-2901 | email Jerry Camuso SSRL Computer and Networking (650) 926-2994 | email Networking Support The Networking group provides connectivity and communications services for SSRL. The services provided by the Networking Support Group include: Local Area Network support for cable and wireless connectivity. Installation and maintenance of network printers and queues. Telephony installations and support. Printing Support The Networking group provides printer maintenance and support for SSRL Beamline Printers and plotters. The following models are supported: HP - Designjet large format plotters HP - Color and B/W Laserjet, Inkjet, Deskjet, Officejet

437

Helper's Network Gazette January 1995  

E-Print Network [OSTI]

Helpers Network Gazette - January 1995 file:///K|/.../Helper's%20Gazette%20Newsletter/Beauty%20and%20the%20Beast%20Helper's%20Gazette%201995-01%20(January)%20.htm[3/31/2013 5:37:01 PM] The Helpers' Network GAZETTE - January 1995 a monthly... no English -- you know, Helpers Network Gazette - January 1995 file:///K|/.../Helper's%20Gazette%20Newsletter/Beauty%20and%20the%20Beast%20Helper's%20Gazette%201995-01%20(January)%20.htm[3/31/2013 5:37:01 PM] they translated [the series] into Arabic...

1995-01-01T23:59:59.000Z

438

Information Thermodynamics on Causal Networks  

Science Journals Connector (OSTI)

We study nonequilibrium thermodynamics of complex information flows induced by interactions between multiple fluctuating systems. Characterizing nonequilibrium dynamics by causal networks (i.e., Bayesian networks), we obtain novel generalizations of the second law of thermodynamics and the fluctuation theorem, which include an informational quantity characterized by the topology of the causal network. Our result implies that the entropy production in a single system in the presence of multiple other systems is bounded by the information flow between these systems. We demonstrate our general result by a simple model of biochemical adaptation.

Sosuke Ito and Takahiro Sagawa

2013-10-31T23:59:59.000Z

439

Power consumption in hybrid access and home networking network  

Science Journals Connector (OSTI)

We compare energy consumptions of access and home networks for GPON, DOCSIS 3.0, GPON EOC, and indoor extensions of POF, HomePNA, PLC, and WiMax. Combined GPON EOC and POF technologies...

Feng, Kuo Chang; Keiser, Gerd; Lee, San-Liang

440

A Biologically Inspired Networking Model for Wireless Sensor Networks  

E-Print Network [OSTI]

Wireless sensor networks (WSNs) have emerged in strategic applications such as target detection, localization, and tracking in battlefields, where the large-scale na- ture renders centralized control prohibitive. In addition, the finite batteries...

Charalambous, Charalambos

2011-02-22T23:59:59.000Z

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Network Infusion to Infer Information Sources in Networks  

E-Print Network [OSTI]

Several models exist for diffusion of signals across biological, social, or engineered networks. However, the inverse problem of identifying the source of such propagated information appears more difficult even in the ...

Feizi, Soheil

2014-12-02T23:59:59.000Z

442

A Content-Based Networking Protocol For Sensor Networks  

E-Print Network [OSTI]

of Colorado Boulder, Colorado 80309-0430 USA {hallcp,carzanig,rosenj,alw}@cs.colorado.edu University-layer communication service. There is no multi-hop network service such as unicast, multicast, anycast, or flooding

Wolf, Alexander L.

443

Green Power Network: Publications  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

News News TVA Seeks 126 MW of Renewables in 2014 December 2013 More News More News Subscribe to E-Mail Update Subscribe to e-mail update Events EPA Webinar - The Power of Aggregated Purchasing: How to Green Your Electricity Supply & Save Money January 15, 2014 1:00-2:00 p.m. ET Previous Webinars More News Features Green Power Market Status Report (2011 Data) Featured Green Power Reports Publications Alphabetical Listing Categorical Listing Chronological Listing Featured Reports The Green Power Network library contains articles and reports on green power, green pricing, and related topics. Whenever possible, we provide a link to publications available online. The publications are grouped by the following topics to help you in your search. If you are aware of other documents that should be added to this list, please notify our Webmaster.

444

Wellbore Integrity Network  

SciTech Connect (OSTI)

In this presentation, we review the current state of knowledge on wellbore integrity as developed in the IEA Greenhouse Gas Programme's Wellbore Integrity Network. Wells are one of the primary risks to the successful implementation of CO{sub 2} storage programs. Experimental studies show that wellbore materials react with CO{sub 2} (carbonation of cement and corrosion of steel) but the impact on zonal isolation is unclear. Field studies of wells in CO{sub 2}-bearing fields show that CO{sub 2} does migrate external to casing. However, rates and amounts of CO{sub 2} have not been quantified. At the decade time scale, wellbore integrity is driven by construction quality and geomechanical processes. Over longer time-scales (> 100 years), chemical processes (cement degradation and corrosion) become more important, but competing geomechanical processes may preserve wellbore integrity.

Carey, James W. [Los Alamos National Laboratory; Bachu, Stefan [Alberta Innovates

2012-06-21T23:59:59.000Z

445

Proactive mobile wireless networks : an infrastructureless wireless network architecture for delay-sensitive applications  

E-Print Network [OSTI]

Infrastructureless wireless networks are an important class of wireless networks that is best suited for scenarios where there is temporary and localized telecommunication demand. Such networks consist of wireless devices ...

Dai, Lillian Lei, 1978-

2008-01-01T23:59:59.000Z

446

Desynchronization of Morris: Lecar Network via Robust Adaptive Artificial Neural Network  

Science Journals Connector (OSTI)

This paper has presented a robust adaptive artificial neural network (ANN) method to desynchronize a network composed of MorrisLecar (ML) ... . During the whole process of desynchronizing the network, the robus...

Yingyuan Chen; Jiang Wang; Xile Wei

2014-01-01T23:59:59.000Z

447

Fair rate assignment in interference limited multi-hop networks  

E-Print Network [OSTI]

Conclusion (Micro-Bu?ered Networks) . . . . . . . . . . .Micro-Bu?ered Networks . . . . . . . . . . . . . . . . . . . . . . . . . . .for wdm-based micro-bu?ered networks . Figure 2.3: A sample

Arisoylu, Mustafa

2006-01-01T23:59:59.000Z

448

Hidden and Uncontrolled On the Emergence of Network Steganographic Threats  

Science Journals Connector (OSTI)

Network steganography is the art of hiding secret information within innocent network transmissions. Recent findings indicate that novel malware is increasingly using network steganography. Similarly, other ma...

Steffen Wendzel; Wojciech Mazurczyk

2014-01-01T23:59:59.000Z

449

Better Buildings Network View | May 2014 | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

May 2014 Better Buildings Network View | May 2014 The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network....

450

Better Buildings Residential Network: Lessons Learned: Peer Exchange...  

Broader source: Energy.gov (indexed) [DOE]

Network: Lessons Learned: Peer Exchange Calls Better Buildings Residential Network: Lessons Learned: Peer Exchange Calls Better Buildings Residential Network: Lessons Learned: Peer...

451

Better Buildings Network View | April 2014 | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

Network View | April 2014 Better Buildings Network View | April 2014 The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings...

452

Better Buildings Network View | June 2014 | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

June 2014 Better Buildings Network View | June 2014 The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network....

453

Trilliant Networks | Open Energy Information  

Open Energy Info (EERE)

Networks Networks Jump to: navigation, search Logo: Trilliant Networks Name Trilliant Networks Address 1100 Island Drive Place Redwood City, California Zip 94065 Sector Efficiency Product Provides utilities with metering communication platform Website http://www.trilliantinc.com/ Coordinates 37.536317°, -122.256385° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.536317,"lon":-122.256385,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

454

Enerlogics Networks | Open Energy Information  

Open Energy Info (EERE)

Enerlogics Networks Enerlogics Networks Jump to: navigation, search Logo: Enerlogics Networks Name Enerlogics Networks Place Pittsburgh, Pennsylvania Product buidling automation control systems to utility software solutions to telecommunication systems development and deployment Phone number 1.866.381.2761 Website http://www.enerlogics.com Coordinates 40.4406248°, -79.9958864° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":40.4406248,"lon":-79.9958864,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

455

Controlled mobility in sensor networks  

E-Print Network [OSTI]

K. Gupta. Optimizing energy-latency trade- o? in sensoras Optimizing Energy-Latency Trade-o? in Sensor NetworksK. Gupta, Optimizing Energy-Latency Trade-o? in Sensor

Sugihara, Ryo

2009-01-01T23:59:59.000Z

456

Green Mobile Networking and Communications  

Science Journals Connector (OSTI)

......AEV) in smart grids. EMF is designed from the following aspects: AEV navigation with wireless sensor networks, smart grid communication architecture for EMF and AEV charging station. The proposed EMF is able to collect the real-time power......

Min Chen; Victor C.M. Leung

2013-08-01T23:59:59.000Z

457

Social networks for lonely objects  

E-Print Network [OSTI]

Visions of ubiquitous computing describe a network of devices that quietly supports human goals, but this may also add complexity to an already frustrating relationship between humans and their electronic objects. As we ...

Kestner, John Anthony

2010-01-01T23:59:59.000Z

458

Complex networks in confined comminution  

Science Journals Connector (OSTI)

The physical process of confined comminution is investigated within the framework of complex networks. We first characterize the topology of the unweighted contact networks as generated by the confined comminution process. We find this process gives rise to an ultimate contact network which exhibits a scale-free degree distribution and small world properties. In particular, if viewed in the context of networks through which information travels along shortest paths, we find that the global average of the node vulnerability decreases as the comminution process continues, with individual node vulnerability correlating with grain size. A possible application to the design of synthetic networks (e.g., sensor networks) is highlighted. Next we turn our attention to the physics of the granular comminution process and examine force transmission with respect to the weighted contact networks, where each link is weighted by the inverse magnitude of the normal force acting at the associated contact. We find that the strong forces (i.e., force chains) are transmitted along pathways in the network which are mainly following shortest-path routing protocols, as typically found, for example, in communication systems. Motivated by our earlier studies of the building blocks for self-organization in dense granular systems, we also explore the properties of the minimal contact cycles. The distribution of the contact strain energy intensity of 4-cycle motifs in the ultimate state of the confined comminution process is shown to be consistent with a scale-free distribution with infinite variance, thereby suggesting that 4-cycle arrangements of grains are capable of storing vast amounts of energy in their contacts without breaking.

David M. Walker; Antoinette Tordesillas; Itai Einav; Michael Small

2011-08-08T23:59:59.000Z

459

E-Print Network 3.0 - active network analysis Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

activity of coupled networks. The neurons... and activity propagation in coupled neural networks from rat cortical cells grown on a micro-electrode array... for parallel activity...

460

E-Print Network 3.0 - area navigation network Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

and Computer... for successful navigation. In this paper, we design and analyze the micro-navigation satellite network that share... in the network. In this paper, we propose...

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

E-Print Network 3.0 - area network umts Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

15 Integrating UMTS and 802.11 WLAN Networks Summary: Integrating UMTS and 802.11 WLAN Networks Muhammad Jaseemuddin Ryerson University, Toronto, Canada... ;Integration...

462

E-Print Network 3.0 - adolescent social networks Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

2011-Present-Co-Investigator, Social Networking Technology... ., Barman-Adhikari, A., & Young, S. D. Internet use, social networking, and HIVAIDS risk for homeless... . (revise...

463

E-Print Network 3.0 - alphabetic bipartite networks Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

No 2 ALPHABETIC BIPARTITE NETWORK (-Bi... . In the last section we conclude and point to possible future works. 12;Alphabetic Bipartite Network (-Bi... ) shows the...

464

E-Print Network 3.0 - adaptive logic networks Sample Search Results  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

University of South Carolina Collection: Engineering 3 Mining Networked Data Nicola Di Mauro and Donato Malerba Summary: Logic Networks 6 it is possible to represent different...

465

E-Print Network 3.0 - achievable network capacity Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

data transmission rate that a network can support. The throughput capacity... of pure ad hoc network models. It is not ... Source: Massachusetts at Amherst, University of -...

466

E-Print Network 3.0 - advanced research network Sample Search...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Dartmouth Collection: Computer Technologies and Information Sciences 4 EEL6935: Wireless Ad Hoc Networks Spring 2007 Summary: EEL6935: Wireless Ad Hoc Networks Spring 2007 Catalog...

467

Transportation Networks for Emergency Evacuations  

SciTech Connect (OSTI)

Evacuation modeling systems (EMS) have been developed to facilitate the planning, analysis, and deployment of emergency evacuation of populations at risk. For any EMS, data such as road network maps, traffic control characteristics, and population distribution play critical roles in delineating emergency zones, estimating population at risk, and determining evacuation routes. There are situations in which it is possible to plan in advance for an emergency evacuation including, for example, an explosion at a chemical processing facility or a radiological accident at a nuclear plant. In these cases, if an accident or a terrorist attack were to happen, then the best evacuation plan for the prevailing network and weather conditions would be deployed. In other instances -for example, the derailment of a train transporting hazardous materials-, there may not be any previously developed plan to be implemented and decisions must be made ad-hoc on if and how to identify and proceed with the best course of action to minimize losses. Although both cases require as a starting point the development of a transportation network model of the area at risk, which must include road capacity and topology, in the latter the available time to generate this network is extremely limited. This time constraint precludes the use of any traditional data gathering methodology and the network generation process has to rely on the use of GIS and stochastic modeling techniques. The generation of these transportation networks in real time is the focus of this entry.

Franzese, Oscar [ORNL; Liu, Cheng [ORNL

2008-01-01T23:59:59.000Z

468

Energy audit of irrigation networks  

Science Journals Connector (OSTI)

The relationship between water and energy in water distribution systems (WDS) has been a growing concern among energy and water experts. Among the different strategies to improve waterenergy efficiency in water distribution networks, energy audits are of paramount importance as they quantify water flow requirements, the amount of energy consumed to meet demand and leakage and friction losses. Previous work has presented the energy audit process for urban WDS and this energy audit is extended to irrigation networks here. This work analyses the most common types of irrigation emitters (sprinklers and pressure compensating and non-pressure compensating drippers), hydrant specifications, irrigation management systems (on-demand or rigid scheduled), and energy losses due to friction in pipes, control valves and irrigation hydrants. The energy audit does not assess whether management of the network is optimal, but analyses the energy consumption. Some of the performance indicators have already been defined for agricultural water networks, some are identical to those of urban WDS, but in addition, a new one is presented that disaggregates the energy dissipated into three terms, energy losses in pipelines, in hydraulic valves and in irrigation hydrants. These indicators show information necessary to better understand the performance of the irrigation network under study, to carry out a deep analysis of energy consumption and to allow for comparison with similar systems. The paper presents the analysis of a real case study conducted on the irrigation network of the garden of the Universidad Politcnica de Valencia.

Miguel A. Pardo; Juan Manzano; Enrique Cabrera; Jorge Garca-Serra

2013-01-01T23:59:59.000Z

469

Peak Oil Food Network | Open Energy Information  

Open Energy Info (EERE)

Network Network Jump to: navigation, search Name Peak Oil Food Network Place Crested Butte, Colorado Zip 81224 Website http://www.PeakOilFoodNetwork. References Peak Oil Food Network[1] LinkedIn Connections This article is a stub. You can help OpenEI by expanding it. The Peak Oil Food Network is a networking organization located in Crested Butte, Colorado, and is open to the general public that seeks to promote the creation of solutions to the challenge of food production impacted by the peak phase of global oil production. Private citizens are encouraged to join and contribute by adding comments, writing blog posts or adding to discussions about food and oil related topics. Peak Oil Food Network can be followed on Twitter at: http://www.Twitter.com/PeakOilFoodNtwk Peak Oil Food Network on Twitter

470

The Cost of Attack in Competing Networks  

E-Print Network [OSTI]

Real-world attacks can be interpreted as the result of competitive interactions between networks, ranging from predator-prey networks to networks of countries under economic sanctions. Although the purpose of an attack is to damage a target network, it also curtails the ability of the attacker, which must choose the duration and magnitude of an attack to avoid negative impacts on its own functioning. Nevertheless, despite the large number of studies on interconnected networks, the consequences of initiating an attack have never been studied. Here, we address this issue by introducing a model of network competition where a resilient network is willing to partially weaken its own resilience in order to more severely damage a less resilient competitor. The attacking network can take over the competitor nodes after their long inactivity. However, due to a feedback mechanism the takeovers weaken the resilience of the attacking network. We define a conservation law that relates the feedback mechanism to the resilie...

Podobnik, B; Lipic, T; Perc, M; Buldu, J M; Stanley, H E

2015-01-01T23:59:59.000Z

471

Community Detection from Location-Tagged Networks  

E-Print Network [OSTI]

Many real world systems or web services can be represented as a network such as social networks and transportation networks. In the past decade, many algorithms have been developed to detect the communities in a network using connections between nodes. However in many real world networks, the locations of nodes have great influence on the community structure. For example, in a social network, more connections are established between geographically proximate users. The impact of locations on community has not been fully investigated by the research literature. In this paper, we propose a community detection method which takes locations of nodes into consideration. The goal is to detect communities with both geographic proximity and network closeness. We analyze the distribution of the distances between connected and unconnected nodes to measure the influence of location on the network structure on two real location-tagged social networks. We propose a method to determine if a location-based community detection...

Liu, Zhi

2015-01-01T23:59:59.000Z

472

Networks and the Epidemiology of Infectious Disease  

E-Print Network [OSTI]

The science of networks has revolutionised research into the dynamics of interacting elements. It could be argued that epidemiology in particular has embraced the potential of network theory more than any other discipline. Here we review the growing body of research concerning the spread of infectious diseases on networks, focusing on the interplay between network theory and epidemiology. The review is split into four main sections, which examine: the types of network relevant to epidemiology; the multitude of ways these networks can be characterised; the statistical methods that can be applied to infer the epidemiological parameters on a realised network; and finally simulation and analytical methods to determine epidemic dynamics on a given network. Given the breadth of areas covered and the ever-expanding number of publications, a comprehensive review of all work is impossible. Instead, we provide a personalised overview into the areas of network epidemiology that have seen the greatest progress in recent ...

Danon, Leon; House, Thomas; Jewell, Chris P; Keeling, Matt J; Roberts, Gareth O; Ross, Joshua V; Vernon, Matthew C

2010-01-01T23:59:59.000Z

473

Phenomenological models of socioeconomic network dynamics  

Science Journals Connector (OSTI)

We study a general set of models of social network evolution and dynamics. The models consist of both a dynamics on the network and evolution of the network. Links are formed preferentially between similar nodes, where the similarity is defined by the particular process taking place on the network. The interplay between the two processes produces phase transitions and hysteresis, as seen using numerical simulations for three specific processes. We obtain analytic results using mean-field approximations, and for a particular case we derive an exact solution for the network. In common with real-world social networks, we find coexistence of high and low connectivity phases and history dependence.

George C. M. A. Ehrhardt; Matteo Marsili; Fernando Vega-Redondo

2006-09-13T23:59:59.000Z

474

NCON: A tensor network contractor for MATLAB  

E-Print Network [OSTI]

A fundamental process in the implementation of any numerical tensor network algorithm is that of contracting a tensor network. In this process, a network made up of multiple tensors connected by summed indices is reduced to a single tensor or a number by evaluating the index sums. This article presents a MATLAB function ncon(), or "Network CONtractor", which accepts as its input a tensor network and a contraction sequence describing how this network may be reduced to a single tensor or number. As its output it returns that single tensor or number. The function ncon() may be obtained by downloading the source of this preprint.

Pfeifer, Robert N C; Singh, Sukhwinder; Vidal, Guifre

2014-01-01T23:59:59.000Z

475

NCON: A tensor network contractor for MATLAB  

E-Print Network [OSTI]

A fundamental process in the implementation of any numerical tensor network algorithm is that of contracting a tensor network. In this process, a network made up of multiple tensors connected by summed indices is reduced to a single tensor or a number by evaluating the index sums. This article presents a MATLAB function ncon(), or "Network CONtractor", which accepts as its input a tensor network and a contraction sequence describing how this network may be reduced to a single tensor or number. As its output it returns that single tensor or number. The function ncon() may be obtained by downloading the source of this preprint.

Robert N. C. Pfeifer; Glen Evenbly; Sukhwinder Singh; Guifre Vidal

2014-02-05T23:59:59.000Z

476

Optimization of synchronization in gradient clustered networks  

E-Print Network [OSTI]

We consider complex clustered networks with a gradient structure, where sizes of the clusters are distributed unevenly. Such networks describe more closely actual networks in biophysical systems and in technological applications than previous models. Theoretical analysis predicts that the network synchronizability can be optimized by the strength of the gradient field but only when the gradient field points from large to small clusters. A remarkable finding is that, if the gradient field is sufficiently strong, synchronizability of the network is mainly determined by the properties of the subnetworks in the two largest clusters. These results are verified by numerical eigenvalue analysis and by direct simulation of synchronization dynamics on coupled-oscillator networks.

Xingang Wang; Liang Huang; Ying-Cheng Lai; Choy Heng Lai

2007-11-23T23:59:59.000Z

477

Social Network and Communications Institutional Change Principle |  

Broader source: Energy.gov (indexed) [DOE]

Network and Communications Institutional Change Principle Network and Communications Institutional Change Principle Social Network and Communications Institutional Change Principle October 8, 2013 - 10:59am Addthis Federal agencies can use social networks and communications to spark and reinforce behavior change for meeting sustainability goals. This principle is based on research findings showing that people and institutions often are strongly influenced by the behaviors and expectations of others. Methods The social network and communications behavior change principle involves informing staff about others' sustainability efforts, especially those that are successful. Methods for social networking and communicating include many internal or external media channels, such as websites, blogs, newsletters, and emails.

478

Proposed Solution:Proposed Solution: The Autonomous Networked Aquatic Microbial Observing SystemThe Autonomous Networked Aquatic Microbial Observing System Networked Aquatic Microbial Observing Systems: an overviewNetworked Aquatic Microbial Observing Sys  

E-Print Network [OSTI]

Proposed Solution:Proposed Solution: The Autonomous Networked Aquatic Microbial Observing SystemThe Autonomous Networked Aquatic Microbial Observing System Networked Aquatic Microbial Observing Systems Ocean Research Goals · Development of autonomous networks of heterogeneous sensors to monitor and sample

Smith, Ryan N.

479

Optimization Online - Energy Savings in Wireless Mesh Networks in ...  

E-Print Network [OSTI]

Jan 24, 2011 ... Abstract: Energy consumption of communication systems is ... Keywords: Energy savings, wireless Mesh Networks, Green networking.

Antonio Capone

2011-01-24T23:59:59.000Z

480

Better Buildings Network View | July-August 2014  

Broader source: Energy.gov [DOE]

The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

Note: This page contains sample records for the topic "network esnet bes" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Extending the Coverage of a 4G Telecom Network Using Hybrid AD-HOC Networks: A Case Study  

Science Journals Connector (OSTI)

Ad-hoc networks that are connected with the infrastructure Internet are named hybrid ad-hoc networks. In 4G communications scenarios, hybrid ad-hoc networks seem to be valuable ... network interfaces, may reach t...

Tnia Calada; Manuel Ricardo

2006-01-01T23:59:59.000Z

482

EIA - Natural Gas Pipeline Network - Network Configuration & System Design  

U.S. Energy Information Administration (EIA) Indexed Site

Network Configuration & System Design Network Configuration & System Design About U.S. Natural Gas Pipelines - Transporting Natural Gas based on data through 2007/2008 with selected updates Network Configuration and System Design Overview | Transmission/Storage | Design Criteria | Importance of Storage| Overall Pipeline System Configuration Overview A principal requirement of the natural gas transmission system is that it be capable of meeting the peak demand of its shippers who have contracts for firm service. To meet this requirement, the facilities developed by the natural gas transmission industry are a combination of transmission pipelines to bring the gas to the market areas and of underground natural gas storage sites and liquefied natural gas (LNG) peaking facilities located in the market areas.

483

Flexible network wireless transceiver and flexible network telemetry transceiver  

DOE Patents [OSTI]

A transceiver for facilitating two-way wireless communication between a baseband application and other nodes in a wireless network, wherein the transceiver provides baseband communication networking and necessary configuration and control functions along with transmitter, receiver, and antenna functions to enable the wireless communication. More specifically, the transceiver provides a long-range wireless duplex communication node or channel between the baseband application, which is associated with a mobile or fixed space, air, water, or ground vehicle or other platform, and other nodes in the wireless network or grid. The transceiver broadly comprises a communication processor; a flexible telemetry transceiver including a receiver and a transmitter; a power conversion and regulation mechanism; a diplexer; and a phased array antenna system, wherein these various components and certain subcomponents thereof may be separately enclosed and distributable relative to the other components and subcomponents.

Brown, Kenneth D. (Grain Valley, MO)

2008-08-05T23:59:59.000Z

484

IAI : Biological Intelligence and Neural Networks John A. Bullinaria, 2005  

E-Print Network [OSTI]

Intelligent Things? 2. What are Neural Networks? 3. What are Artificial Neural Networks used for? 4. Introduction to Biological Neural Networks 5. Introduction to Artificial Neural Networks 6. Some Current Artificial Neural Networks Applications 7. Limitations of Artificial Neural Network Systems #12;W3-2 How do

Bullinaria, John

485

AITA : Biological Intelligence and Neural Networks John A. Bullinaria, 2003  

E-Print Network [OSTI]

Intelligent Things? 2. What are Neural Networks? 3. What are Artificial Neural Networks used for? 4. Introduction to Biological Neural Networks 5. Introduction to Artificial Neural Networks 6. Some Current Artificial Neural Networks Applications 7. Limitations of Artificial Neural Network Systems #12;W3s1-2 How do

Bullinaria, John

486

Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks  

Science Journals Connector (OSTI)

...Theme Issue Complex network theory and the brain compiled and edited by David Papo, Javier...neuronal networks and large-scale human brain networks Petra E. Vertes 1 Aaron Alexander-Bloch...Theme Issue Complex network theory and the brain . Rich clubs arise when nodes that are...

2014-01-01T23:59:59.000Z

487

Auto-Networking Technologies for IPv6 Mobile Ad Hoc Networks  

E-Print Network [OSTI]

Auto-Networking Technologies for IPv6 Mobile Ad Hoc Networks Jaehoon Jeong, Jungsoo Park for IPv6 mobile ad hoc networks. The auto-networking technologies consist of IPv6 unicast address. These technologies are based on IPv6's inherent autoconfiguration facility, which can provide ad hoc users

Jeong, Jaehoon "Paul"

488

Random Walks and Electrical Networks Electrical Network Calculations in Random Walks in  

E-Print Network [OSTI]

Random Walks and Electrical Networks Electrical Network Calculations in Random Walks in Random 2/4/2008 1 / 23 #12;Random Walks and Electrical Networks Much of this talk is based on the book Random Walks and Electric Networks by Peter G. Doyle and J. Laurie Snell. Free download available at http

Peterson, Jonathon

489

Bounds on the Gain of Network Coding and Broadcasting in Wireless Networks  

E-Print Network [OSTI]

1 Bounds on the Gain of Network Coding and Broadcasting in Wireless Networks Junning Liu , Dennis the possibility of network coding and broadcasting in their model, and recent work has suggested network coding and broadcasting in a )10 random topology that the throughput scales as ¥§¦¨¤©2

Massachusetts at Amherst, University of

490

Definition: Customer System Communications Network | Open Energy  

Open Energy Info (EERE)

System Communications Network System Communications Network Jump to: navigation, search Dictionary.png Customer System Communications Network The communications network or networks between the customers' premise and the utility, designed to provide two-way communications between customer systems and utility information systems. These networks can utilize wired or wireless connections, and can be utility-owned or provided as services by a third party.[1] Related Terms system References ↑ https://www.smartgrid.gov/category/technology/customer_system_communications_network [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitions|Template:BASEPAGENAME]] Retrieved from "http://en.openei.org/w/index.php?title=Definition:Customer_System_Communications_Network&oldid=480382"

491

Clock synchronization for mobile ad hoc networks  

E-Print Network [OSTI]

As mobile networking advances, there is a need for services such as clock synchronization that improve performance and support the development of higher-level applications. This can be achieved by adapting existing algorithms (such as the Network...

Chandra, Rajan

2013-02-22T23:59:59.000Z

492

Semantic associative network for text analysis (SANTA)  

E-Print Network [OSTI]

Based on theories of associations, the Semantic Associative Network for Text Analysis (SANTA) has been developed. Nodes in the network represent words and links between nodes represent the association strengths between them. The links are adjusted...

Airhart, Robert William

2012-06-07T23:59:59.000Z

493

Homological scaffolds of brain functional networks  

Science Journals Connector (OSTI)

...are credited. Homological scaffolds of brain functional networks G. Petri 1 P. Expert...Clinical Neuroimaging Laboratory, Division of Brain Sciences, Imperial College London...study the characteristics of functional brain networks at the mesoscopic level from a...

2014-01-01T23:59:59.000Z

494

Evolving networks with bimodal degree distribution  

Science Journals Connector (OSTI)

Networks with bimodal degree distribution are most robust to targeted and random attacks. We present a model for constructing a network with bimodal degree distribution. The procedure adopted is to add nodes ...

Abhijeet R. Sonawane; A. Bhattacharyay; M. S. Santhanam

2012-04-01T23:59:59.000Z

495

A Novel Artificial Neural Network Learning Algorithm  

Science Journals Connector (OSTI)

The unit feedback recursive neural network model which is widely used at present has been analyzed. It makes the unit feedback recursive neural network have the same dynamic process and time delay characterist...

Tinggui Li; Qinhui Gong

2013-01-01T23:59:59.000Z

496

Artificial Neural Network Resistance to Incomplete Data  

Science Journals Connector (OSTI)

This paper presents results obtained in experiments related to artificial neural networks. Artificial neural networks have been trained with delta-bar-delta ... the experiment was to observe how long will neural

Magdalena Alicja Tkacz

2006-01-01T23:59:59.000Z

497

Virtual infrastructure for wireless ad hoc networks  

E-Print Network [OSTI]

One of the most significant challenges introduced by ad hoc networks is coping with the unpredictable deployment, uncertain reliability, and erratic communication exhibited by emerging wireless networks and devices. The ...

Gilbert, Seth, 1976-

2007-01-01T23:59:59.000Z

498

Trends in Mobile Multimedia and Networks  

Science Journals Connector (OSTI)

NTT DoCoMo is the company to DO COmmunications over the MObile Network. It reached 43 million subscribers in Japan, early 2003. This presentation covers the multimedia services over mobile networks and give ...

Minoru Etoh

2003-01-01T23:59:59.000Z

499

Advanced battery modeling using neural networks  

E-Print Network [OSTI]

battery models are available today that can accurately predict the performance of the battery system. This thesis presents a modeling technique for batteries employing neural networks. The advantage of using neural networks is that the effect of any...

Arikara, Muralidharan Pushpakam

1993-01-01T23:59:59.000Z

500

Local Area Networks - Applications to Energy Management  

E-Print Network [OSTI]

LOCAL AREA NETWORKS - APPLICATIONS TO MERCY MANAGmNT Advanced BRUCE M. BAKKEN Software bfanager Micro Syatems Corporation Milwaukee, WI ABSTRACT One of the newest advances in computer technology is the Local Area Network. Its many...

Bakken, B. M.

1984-01-01T23:59:59.000Z