Dynamic flow scheduling technique for load balancing in fat-tree data center networks

Wen Hsuan Liang, Dun Wei Cheng, Chih Wei Hsu, Chia Wei Lee, Chih Heng Keand, Albert Y. Zomaya, Sun Yuan Hsieh*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

3 Scopus citations

Abstract

Modern data center networks for a fat-tree topology typically adopt a multirooted hierarchical tree structure to achieve multiple-path capability and increase bisection bandwidth. However, the performance of a data center network highly depends on the routing protocols. Conventional routing protocols are unsuitable for modern data center topologies because they lack multiple-path routing support. Another crucial concern in data center networks is load balancing. Certain routing protocol limitations could lead to overloaded or underloaded utilization of a link, thereby considerably reducing the performance of a data center network. Therefore, we present a genetic algorithm (GA)-based dynamic load-balancing routing algorithm, which is heuristic and involves the use of a centralized scheduling technique. This algorithm mainly uses a GA to search for optimal solutions. We implement our algorithm in an OpenFlow controller RYU and Mininet emulator, which is based on software-defined networking architecture. Our evaluation results revealed that our algorithm can effectively achieve load balancing and increase bisection bandwidth.

Original languageEnglish
Pages (from-to)491-503
Number of pages13
JournalInternational Journal of Performability Engineering
Volume17
Issue number6
DOIs
StatePublished - 06 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 Totem Publisher, Inc. All rights reserved.

Keywords

  • Data center networks
  • Fat-tree
  • Genetic algorithms
  • Routing algorithms
  • Software -defined networking

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