A genetic-based load balancing algorithm in OpenFlow network

Li Der Chou, Yao Tsung Yang, Yuan Mao Hong, Jhih Kai Hu, Bill Jean

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

28 Scopus citations

Abstract

Load balancing service is essential for distributing workload across server farms or data centers and mainly provided by dedicated hardware. In recent years, the concept of Software-Defined Networking (SDN) has been applied successfully in the real network environment, especially by OpenFlow designs. This paper presents an OpenFlow-based load balancing system with the genetic algorithm. This system can distribute large data from clients to different servers more efficiently according to load balancing policies. Furthermore, with the pre-configured flow table entries, each flow can be directed in advance. Once the traffic burst or server loading increased suddenly, the proposed genetic algorithm can help balance workload of server farms. The experiments demonstrate the better performance of the proposed method compared to other approaches.

Original languageEnglish
Title of host publicationAdvanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013
Pages411-417
Number of pages7
DOIs
StatePublished - 2014
EventAdvanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013 - , Taiwan
Duration: 23 Aug 201325 Aug 2013

Publication series

NameLecture Notes in Electrical Engineering
Volume260 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceAdvanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013
Country/TerritoryTaiwan
Period23/08/1325/08/13

Keywords

  • Genetic algorithm
  • Load balancing
  • OpenFlow
  • Software-defined networking

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