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Performance prediction technology for agent-based resource management in grid environments
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Cao, J., Jarvis, Stephen A., Spooner, Daniel P., Turner, James D. and Nudd, G. R. (2001) Performance prediction technology for agent-based resource management in grid environments. In: Proceedings of the 11th IEEE International Heterogeneous Computing Workshop, Ft. Lauderdale, FL, USA, 15-19 Apr 2001. Published in: Parallel and Distributed Processing Symposium., Proceedings International, IPDPS 2002 ISBN 0769515738.
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Official URL: http://dx.doi.org/10.1109/IPDPS.2002.1015660
Abstract
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.
Item Type: | Conference Item (Paper) | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Journal or Publication Title: | Parallel and Distributed Processing Symposium., Proceedings International, IPDPS 2002 | ||||
Publisher: | IEEE | ||||
ISBN: | 0769515738 | ||||
Official Date: | 2001 | ||||
Dates: |
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Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Date of first compliant deposit: | 28 July 2016 | ||||
Conference Paper Type: | Paper | ||||
Title of Event: | Proceedings of the 11th IEEE International Heterogeneous Computing Workshop | ||||
Type of Event: | Workshop | ||||
Location of Event: | Ft. Lauderdale, FL, USA | ||||
Date(s) of Event: | 15-19 Apr 2001 |
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