The impact of network model on performance of load-balancing

Kensuke Fukuda, Toshio Hirotsu, Satoshi Kurihara, Osamu Akashi, Shin Ya Sato, Toshiharu Sugawara

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

We discuss the applicability of the degree of an agent-the number of links among neighboring agents- to load-balancing for the agent selection and deployment problem. We first introduce agent deployment algorithm that is useful in the design of MAS for loadbalancing. Then we propose an agent selection algorithm, which suggests the strategy for selecting appropriate agents to collaborate with. This algorithm only requires the degree of a server agent and the degrees of the node neighboring the server agent, without global information about network structure. Through simulation of several topologies reproduced by the theoretical network models, we show that the use of the local topological information significantly improves the fairness of the servers.

Original languageEnglish
Title of host publicationEmergend Intelligence of Networked Agents
EditorsAkira Namatame, Hideyuki Nakashima, Satoshi Kurihara
Pages23-37
Number of pages15
DOIs
Publication statusPublished - 2007 May 8
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume56
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Fukuda, K., Hirotsu, T., Kurihara, S., Akashi, O., Sato, S. Y., & Sugawara, T. (2007). The impact of network model on performance of load-balancing. In A. Namatame, H. Nakashima, & S. Kurihara (Eds.), Emergend Intelligence of Networked Agents (pp. 23-37). (Studies in Computational Intelligence; Vol. 56). https://doi.org/10.1007/978-3-540-71075-2_3