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Task Cost Based Approach for Grid Service Reliability Modeling on Fault Recovery

In recent year, solving Grid service reliability are not easy tasks because of the complexity and large scale of the system and resources. While concerning on large scale system, large subtasks requires timeconsuming computation, therefore the reliability of grid service could be rather low. Our paper tries to focus on maximizing reliability and minimizing cost of grid resources. In the existing system all researchers focused on the remote node fault recovery where more waste is consumed on time and resources. Furthermore those systems did not incorporate the fault recovery and the practical constraints of grid resource on optimization. Resultantly our paper considers the Local Node Fault Recovery mechanism into grid systems, and presents a solution to simultaneously maximize the grid service reliability and minimizing the cost. Our proposed Grid Service Reliability & Node Recovery (GSRNR) mechanism considers some practical constraints such as the life times of subtasks, the numbers of recoveries performed in grid nodes. Presuming the proposed grid service reliability model, a multi-objective task cost scheduling optimization model is presented, and Min Max cost scheduling algorithm is developed to solve it effectively.