• DocumentCode
    2733857
  • Title

    Comparing Configurable Parameters of Swarm Intelligence Algorithms for Dynamic Load Balancing

  • Author

    Sesum-Cavic, Vesna ; Kühn, Eva

  • Author_Institution
    Inst. of Comput. Languages, Vienna Univ. of Technol., Vienna, Austria
  • fYear
    2010
  • fDate
    27-28 Sept. 2010
  • Firstpage
    42
  • Lastpage
    49
  • Abstract
    A main challenge on today´s distributed systems is to cope with huge amounts of load. An important research issue is to distribute load across enterprise boundaries in highly heterogeneous environments. However, intelligent and adaptive load balancing problem is a complex problem and requires both intelligent algorithms and approaches. In this paper, we present the first findings of a novel approach towards load balancing, based on bee intelligence. The approach defines a generic architecture called SILBA (self initiative load balancing agents) which allows the exchange of different algorithms through simple plugging techniques. Six algorithms were developed, both unintelligent and intelligent ones, compared and performance benchmarks on both a cluster of virtual nodes and the Amazon EC2 cloud demonstrate promising benefits of the bee based algorithm.
  • Keywords
    distributed processing; mobile agents; multi-agent systems; optimisation; resource allocation; Amazon EC2; SILBA; bee based algorithm; bee intelligence; distributed system; dynamic load balancing; generic architecture; heterogeneous environment; plugging technique; selfinitiative load balancing agent; swarm intelligence algorithm; virtual node; Benchmark testing; Clustering algorithms; Complexity theory; Gallium; Load management; Receivers; Routing; autonomouos agents; load balancing; self-organization; swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Self-Adaptive and Self-Organizing Systems Workshop (SASOW), 2010 Fourth IEEE International Conference on
  • Conference_Location
    Budapest
  • Print_ISBN
    978-1-4244-8684-7
  • Type

    conf

  • DOI
    10.1109/SASOW.2010.12
  • Filename
    5729593