The impact of network model on performance of load-balancing

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

研究成果: Chapter

2 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルEmergend Intelligence of Networked Agents
編集者Akira Namatame, Hideyuki Nakashima, Satoshi Kurihara
ページ23-37
ページ数15
DOI
出版ステータスPublished - 2007 5 8
外部発表はい

出版物シリーズ

名前Studies in Computational Intelligence
56
ISSN(印刷版)1860-949X

ASJC Scopus subject areas

  • 人工知能

フィンガープリント

「The impact of network model on performance of load-balancing」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル