Agent-based resource management for grid computing

Junwei Cao, Daniel P. Spooner, James D. Turner, Stephen A. Jarvis, Darren J. Kerbyson, Subhash Saini, Graham R. Nudd

Research output: Chapter in Book/Report/Conference proceedingConference contribution

37 Citations (Scopus)

Abstract

It is envisaged that the grid infrastructure will be a large-scale distributed software system that will provide high-end computational and storage capabilities to differentiated users. A number of distributed computing technologies are being applied to grid development work, including CORBA and Jini. In this work, we introduce an A4 (Agile Architecture and Autonomous Agents) methodology, which can be used for resource management for grid computing. An initial system implementation utilises the performance prediction techniques of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on local grid resources. At the meta-level, a hierarchy of identical agents is used to provide an abstraction of the system architecture. Each agent is able to cooperate with other agents to provide service advertisement and discovery to schedule applications that need to utilise grid resources. A performance monitor and advisor (PMA) is in development to optimize the performance of agent behaviours.

Original languageEnglish
Title of host publication2nd IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid 2002
PublisherIEEE Computer Society
Pages350
Number of pages1
ISBN (Print)0769515827, 9780769515823
DOIs
Publication statusPublished - 2002
Event2nd IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid 2002 - Berlin, Germany
Duration: 21 May 200224 May 2002

Publication series

Name2nd IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid 2002

Conference

Conference2nd IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid 2002
Country/TerritoryGermany
CityBerlin
Period21/05/0224/05/02

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software
  • Electrical and Electronic Engineering

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