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Title: Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks

Abstract

Many next-generation e-science applications need fast and reliable transfer of large volumes of data with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks. One prominent issue in such network environments with large footprints is that node and link failures are inevitable, hence potentially degrading the quality of data transfer. We consider two generic types of bandwidth reservation requests (BRRs) concerning data transfer reliability: (i) to achieve the highest data transfer reliability under a given data transfer deadline, and (ii) to achieve the earliest data transfer completion time while satisfying a given data transfer reliability requirement. We propose two periodic bandwidth reservation algorithms with rigorous optimality proofs to optimize the scheduling of individual BRRs within BRR batches. The efficacy of the proposed algorithms is illustrated through extensive simulations in comparison with scheduling algorithms widely adopted in production networks in terms of various performance metrics.

Authors:
 [1];  [2];  [3];  [4]
  1. California State Univ. Dominguez Hills, Carson, CA (United States)
  2. Montclair State Univ., NJ (United States)
  3. New Jersey Inst. of Technology, Newark, NJ (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
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:
1393122
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Computer Networks
Additional Journal Information:
Journal Volume: 113; Journal Issue: C; Journal ID: ISSN 1389-1286
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Zuo, Liudong, Zhu, Michelle M., Wu, Chase Q., and Zurawski, Jason. Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks. United States: N. p., 2016. Web. doi:10.1016/j.comnet.2016.11.003.
Zuo, Liudong, Zhu, Michelle M., Wu, Chase Q., & Zurawski, Jason. Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks. United States. doi:10.1016/j.comnet.2016.11.003.
Zuo, Liudong, Zhu, Michelle M., Wu, Chase Q., and Zurawski, Jason. Tue . "Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks". United States. doi:10.1016/j.comnet.2016.11.003.
@article{osti_1393122,
title = {Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks},
author = {Zuo, Liudong and Zhu, Michelle M. and Wu, Chase Q. and Zurawski, Jason},
abstractNote = {Many next-generation e-science applications need fast and reliable transfer of large volumes of data with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks. One prominent issue in such network environments with large footprints is that node and link failures are inevitable, hence potentially degrading the quality of data transfer. We consider two generic types of bandwidth reservation requests (BRRs) concerning data transfer reliability: (i) to achieve the highest data transfer reliability under a given data transfer deadline, and (ii) to achieve the earliest data transfer completion time while satisfying a given data transfer reliability requirement. We propose two periodic bandwidth reservation algorithms with rigorous optimality proofs to optimize the scheduling of individual BRRs within BRR batches. The efficacy of the proposed algorithms is illustrated through extensive simulations in comparison with scheduling algorithms widely adopted in production networks in terms of various performance metrics.},
doi = {10.1016/j.comnet.2016.11.003},
journal = {Computer Networks},
issn = {1389-1286},
number = C,
volume = 113,
place = {United States},
year = {2016},
month = {11}
}