Time-Series Forecast Modeling on High-Bandwidth Network Measurements

doi:10.1007/s10723-016-9368-9

Title: Time-Series Forecast Modeling on High-Bandwidth Network Measurements

Full Record
Other Related Research

Abstract

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and the AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.

Authors:

Yoo, Wucherl ^[1]; Sim, Alex ^[1]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Publication Date:: Fri Jun 24 00:00:00 EDT 2016

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)

OSTI Identifier:: 1377437

Grant/Contract Number:: AC02-05CH11231

Resource Type:: Journal Article: Accepted Manuscript

Journal Name:: Journal of Grid Computing

Additional Journal Information:: Journal Volume: 14; Journal Issue: 3; Journal ID: ISSN 1570-7873

Publisher:: Springer

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; data modeling; time series; prediction model; network measurements; network traffic

Citation Formats


                    Yoo, Wucherl, and Sim, Alex. Time-Series Forecast Modeling on High-Bandwidth Network Measurements.  United States: N. p., 2016. 
        Web.  doi:10.1007/s10723-016-9368-9.

Copy to clipboard


                    Yoo, Wucherl, & Sim, Alex. Time-Series Forecast Modeling on High-Bandwidth Network Measurements.  United States.  doi:10.1007/s10723-016-9368-9.

Copy to clipboard


                    Yoo, Wucherl, and Sim, Alex. Fri .  
        "Time-Series Forecast Modeling on High-Bandwidth Network Measurements".  United States.  
        doi:10.1007/s10723-016-9368-9.  https://www.osti.gov/servlets/purl/1377437.

Copy to clipboard


                    
@article{osti_1377437,

  title        = {Time-Series Forecast Modeling on High-Bandwidth Network Measurements},

  author       = {Yoo, Wucherl and Sim, Alex},

  abstractNote = {With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and the AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.},

  doi          = {10.1007/s10723-016-9368-9},

  journal      = {Journal of Grid Computing},

  number       = 3,

  volume       = 14,

  place        = {United States},

  year         = {Fri Jun 24 00:00:00 EDT 2016},

  month        = {Fri Jun 24 00:00:00 EDT 2016}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

DOI: 10.1007/s10723-016-9368-9

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 2 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar records in OSTI.GOV collections:

Identification of periods of clear sky irradiance in time series of GHI measurements

Journal Article Reno, Matthew J. ; Hansen, Clifford W. - Renewable Energy

In this study, we present a simple algorithm for identifying periods of time with broadband global horizontal irradiance (GHI) similar to that occurring during clear sky conditions from a time series of GHI measurements. Other available methods to identify these periods do so by identifying periods with clear sky conditions using additional measurements, such as direct or diffuse irradiance. Our algorithm compares characteristics of the time series of measured GHI with the output of a clear sky model without requiring additional measurements. We validate our algorithm using data from several locations by comparing our results with those obtained from amore »« less
Cited by 10
DOI: 10.1016/j.renene.2015.12.031

Full Text Available
High pressure shock tube ignition delay time measurements during oxy-methane combustion with high levels of CO ₂ dilution

Journal Article Pryor, Owen ; Barak, Samuel ; Lopez, Joseph ; ... - Journal of Energy Resources Technology

For this study, ignition delay times and methane species time-histories were measured for methane/O ₂ mixtures in a high CO ₂ diluted environment using shock tube and laser absorption spectroscopy. The experiments were performed between 1300 K and 2000 K at pressures between 6 and 31 atm. The test mixtures were at an equivalence ratio of 1 with CH ₄ mole fractions ranging from 3.5% -5% and up to 85% CO ₂ with a bath of argon gas as necessary. The ignition delay times and methane time histories were measured using pressure, emission, and laser diagnostics. Predictive ability of twomore »« less
Cited by 1
DOI: 10.1115/1.4036254

Full Text Available
High Pressure Shock Tube Ignition Delay Time Measurements During Oxy-Methane Combustion With High Levels of CO ₂ Dilution

Journal Article Pryor, Owen ; Barak, Samuel ; Lopez, Joseph ; ... - Journal of Energy Resources Technology

Ignition delay times and methane species time-histories were measured for methane/O2 mixtures in a high CO2 diluted environment using shock tube and laser absorption spectroscopy. The experiments were performed between 1300 K and 2000 K at pressures between 6 and 31 atm. The test mixtures were at an equivalence ratio of 1 with CH4 mole fractions ranging from 3.5% -5% and up to 85% CO2 with a bath of argon gas as necessary. The ignition delay times and methane time histories were measured using pressure, emission, and laser diagnostics. Predictive ability of two literature kinetic mechanisms (GRI 3.0 and ARAMCOmore »« less
Cited by 1
DOI: 10.1115/1.4036254

Full Text Available
A high-order multiscale finite-element method for time-domain acoustic-wave modeling

Journal Article Gao, Kai ; Fu, Shubin ; Chung, Eric T. - Journal of Computational Physics

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructsmore »« less
DOI: 10.1016/j.jcp.2018.01.032
A time projection chamber for high accuracy and precision fission cross-section measurements

Journal Article Heffner, M. ; Asner, D. M. ; Baker, R. G. ; ... - Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment

The fission Time Projection Chamber (fissionTPC) is a compact (15 cm diameter) two-chamber MICROMEGAS TPC designed to make precision cross-section measurements of neutron-induced fission. The actinide targets are placed on the central cathode and irradiated with a neutron beam that passes axially through the TPC inducing fission in the target. The 4π acceptance for fission fragments and complete charged particle track reconstruction are powerful features of the fissionTPC which will be used to measure fission cross-sections and examine the associated systematic errors. This study provides a detailed description of the design requirements, the design solutions, and the initial performance ofmore » the fissionTPC.« less
Cited by 10
DOI: 10.1016/j.nima.2014.05.057

Full Text Available

Similar Records