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Grid computing is already a mainstream paradigm for resource-intensive scientific applications, but it also becomes the useful model for enterprise applications. The grid enables resource sharing and dynamic allocation of computational resources, thus increasing access to distributed data, promoting operational flexibility and collaboration and allowing service providers to scale efficiently to meet variable demands. Grid computing requires an effective allocation for the better utilization of the dynamic resources. The execution of user processes must simultaneously satisfy both job execution constraints and system usage policies. Although many scheduling techniques for various computing system exist, traditional scheduling systems are inappropriate for scheduling tasks into grid resources.
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