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Group Participation Game Strategy for Resource Allocation in Cloud Computing

Abstract : Based on the characteristics of cloud—resources belonging to the same institution and independent resource pool, we proposed a model for the complex task-resource and task-task interactions in cloud by game theory, and proved the existence of Nash equilibrium in the game. In this game model, every task selects resources by itself, rather than the resources are allocated by cloud system. We propose two cloud resource allocation game models—CT-RAG and CS-RAG. A new cloud resource allocation strategy—Group Participation Game Strategy (GPGS) is proposed based on these two game models. We also find out and analyze the equilibrium state of the game with GPGS. The theory analysis shows that GPGS can reduce the total cost of the system in the condition that all tasks/subtasks are rational. Simulation compares Nash, GPGS, Opt and “Round-Robin”. The results of evaluation show that the GPGS is better.
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Weifeng Sun, Danchuang Zhang, Ning Zhang, Qingqing Zhang, Tie Qiu. Group Participation Game Strategy for Resource Allocation in Cloud Computing. 11th IFIP International Conference on Network and Parallel Computing (NPC), Sep 2014, Ilan, Taiwan. pp.294-305, ⟨10.1007/978-3-662-44917-2_25⟩. ⟨hal-01403096⟩



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