Performance prediction technology for agent-based resource management in grid environments

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


  • Junwei Cao
  • D. P. Spooner
  • J. D. Turner
  • D. J. Kerbyson
  • G. R. Nudd

Colleges, School and Institutes

External organisations

  • University of Warwick
  • High Performance Systems Group
  • Los Alamos National Laboratory


Resource management constitutes an important infrastructural component of a computational grid environment. The aim of grid resource management is to efficiently schedule applications over the available resources provided by the supporting grid architecture. Such goals within the high performance community rely, in part, on accurate performance prediction capabilities. This paper introduces a resource management infrastructure for grid computing environments. The technique couples application performance prediction with a hierarchical multi-agent system. An initial system implementation utilises the performance prediction capabilities of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on local grid resources. The validation results show that a high level of accuracy can be obtained, that cross-platform comparisons can be easily undertaken, and that the estimates can be evaluated rapidly. A hierarchy of homogeneous agents are used to provide a scalable and adaptable abstraction of the grid system architecture. An agent is a representative of a local grid resource and is considered to be both a service provider and a service requestor. Agents are organised into a hierarchy and cooperate to provide service advertisement and discovery. A performance monitor and advisor has been developed to optimise the performance of the agent system. A case study with corresponding experimental results are included to demonstrate the efficiency of the resource management and scheduling system. The main features of the system include: hard quality of service support using PACE performance prediction capabilities; agent-based dynamic resource advertisement and discovery capabilities; simulation-based quantitative grid performance analysis and user-oriented scheduling of local grid resources.

Bibliographic note

Funding Information: This work is sponsored in part by grants from the NASA AMES Research Centre (administered by USARDSG, contract no. N68171-01-C-9012) and the EPSRC (contract no. GR/R47424/01). Publisher Copyright: © 2002 IEEE.


Original languageEnglish
Title of host publicationProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002
Publication statusPublished - 2002
Event16th International Parallel and Distributed Processing Symposium, IPDPS 2002 - Ft. Lauderdale, United States
Duration: 15 Apr 200219 Apr 2002

Publication series

NameProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002


Conference16th International Parallel and Distributed Processing Symposium, IPDPS 2002
Country/TerritoryUnited States
CityFt. Lauderdale