Ontology-Based Intelligent Agent for Grid Resource Management
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
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As demand and supply of Grid resources in Grid computing environments increases rapidly, many Grid researchers have taken particular interest in efficient management of Grid resources. In this paper, a user demand prediction-based resource management model (UDPRMM), which uses the user demand trend of Grid resources as a critical management factor, is proposed. This paper introduces a user demand prediction approach with historical user demands and aims for effective Grid resource management through transaction management between resource users and resource suppliers. For performance evaluation with accuracy and reliability, the UDPRMM is compared with the user demand fixed-based resources management model (UDFRMM) and the user demand random-based resources management model (UDRRMM). The UDPRMM demonstrates improvement greater than 70% with regard Grid resource transactions and greater than 16% with regard to Grid resource transaction quantities in comparison with the UDFRMM and the UDRRMM. In evaluation, the UDPRMM reduces delay time by 21%, over that of the UDFRMM, and 19% over that of the UDRRMM. The empirical results demonstrate the usefulness of the UDPRMM with effective economics-based resource management.