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Imprecise input data imposes special challenges to grid scheduling. This paper introduces a novel scheduler based on fuzzy optimization called IP-FULL-FUZZY which considers uncertainties of both application demands and of resource availability. The effectiveness of the proposed scheduler is compared to that of three non-fuzzy schedulers, as well as to that of a fuzzy scheduler which considers only...
Grids involve coordinated resource sharing and problem solving in heterogeneous dynamic environments to meet the needs of a generation of researchers requiring large amounts of bandwidth and more powerful computational resources. The lack of resource ownership by grid schedulers and fluctuations in resource availability require mechanisms which will enable grids to adjust themselves to cope with fluctuations...
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