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Article type: Research Article
Authors: Cao, Junwei | Jarvis, Stephen A. | Saini, Subhash | Kerbyson, Darren J. | Nudd, Graham R.
Affiliations: Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Tel.: +44 24 7652 2863; Fax: +44 24 7657 3024; E-mail: [email protected] | NASA Ames Research Centre, Moffett Field, California, USA | Modelling, Algorithms, and Informatics Group, Los Alamos National Laboratory, USA
Abstract: Resource management is an important component of a grid computing infrastructure. The scalability and adaptability of such systems are two key challenges that must be addressed. In this work an agent-based resource management system, ARMS, is implemented for grid computing. ARMS utilises the performance prediction techniques of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on a local grid resource. At the meta-level, a hierarchy of homogeneous agents are used to provide a scalable and adaptable abstraction of the system architecture. Each agent is able to cooperate with other agents and thereby provide service advertisement and discovery for the scheduling of applications that need to utilise grid resources. A case study with corresponding experimental results is included to demonstrate the efficiency of the resource management and scheduling system.
Journal: Scientific Programming, vol. 10, no. 2, pp. 135-148, 2002
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