Flexible service selection with user-specific QoS support in service-oriented architecture
Journal of Network and Computer Applications
Runtime estimation using the case-based reasoning approach for scheduling in a grid environment
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
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One of the main focuses of Grid computing is solving resource-sharing problems in multi-institutional virtual organizations. In such heterogeneous and distributed environments, selecting the best resource to run a job is a complex task. The solutions currently employed still present numerous challenges and one of them is how to let users know when a job will finish. Consequently, reserve in advance remains unavailable. This article presents a new approach, which makes predictions for job execution time in Grid by applying the case-based reasoning paradigm. The work includes the development of a new case retrieval algorithm involving relevance sequence and similarity degree calculations. The prediction model is part of a multi-agent system that selects the best resource of a computational Grid to run a job. Agents representing candidate resources for job execution make predictions in a distributed and parallel manner. The technique presented here can be used in Grid environments at operation time to assist users with batch job submissions. Experimental results validate the prediction accuracy of the proposed mechanisms, and the performance of our case retrieval algorithm. Copyright © 2006 John Wiley & Sons, Ltd.