A study of the contribution made by evolutionary learning on dynamic load-balancing problems in distributed computing systems

A computer simulation model that investigated the contribution made by evolutionary learning techniques on load-balancing problems was proposed. Three parameters for controlling the load-balancing activity of a node were used. The system was tested in different distributed systems, including differe...

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Published inExpert systems with applications Vol. 34; no. 1; pp. 357 - 365
Main Authors Chen, Jong-Chen, Liao, Guo-Xun, Hsie, Jr-Sung, Liao, Cheng-Hua
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 2008
Subjects
Dynamic load-balancing
Evolutionary algorithm
Heterogeneously distributed system
System simulation
System simulation
Dynamic load-balancing
Heterogeneously distributed system
Evolutionary algorithm
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Summary:A computer simulation model that investigated the contribution made by evolutionary learning techniques on load-balancing problems was proposed. Three parameters for controlling the load-balancing activity of a node were used. The system was tested in different distributed systems, including different processing and communication speeds as well as network structures. Our experimental results showed that the system demonstrated an effective learning capability in balancing load among different processing nodes. It also showed that each of these three parameters played an important role in contributing to load-balancing, and that the system performance increased upon increasing the number of parameter changes simultaneously. The contribution made by evolutionary learning was significant as the variety of node processing speeds increased.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2006.09.036