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An Intelligent Agent based Grid Scheduler with Enhanced Fault Tolerance

In large-scale grid platforms, providing fault-tolerance for users is always a challenging task because of the uncertainty of network resources. In this paper, we present an intelligent agent based meta-scheduler, which is aiming at improving the fault-tolerance of grid systems when running user’s application. The proposed meta-scheduler is designed as an extendable framework, which allows plugging in multiple scheduling policies for deal with different scenarios. The agent-based scheduling framework enables grid systems to deploy their local schedulers in a flexible manner. Extensive experiments are conducted to investigate the performance of the proposed meta-scheduler, and the results show that it is effective to provide enhanced dependability for grid users, especially when the system is across multiorganization.