A game-theoretic method of fair resource allocation for cloud computing services

  • Authors:

  • Guiyi Wei;Athanasios V. Vasilakos;Yao Zheng;Naixue Xiong

  • Affiliations:

  • Zhejiang Gongshang University, Hangzhou, People's Republic of China;National Technical University of Athens, Athens, Greece;Zhejiang University, Hangzhou, People's Republic of China;Department of Computer Science, Georgia State University, Atlanta, USA

  • Venue:
  • The Journal of Supercomputing
  • Year:
  • 2010

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Abstract

As cloud-based services become more numerous and dynamic, resource provisioning becomes more and more challenging. A QoS constrained resource allocation problem is considered in this paper, in which service demanders intend to solve sophisticated parallel computing problem by requesting the usage of resources across a cloud-based network, and a cost of each computational service depends on the amount of computation. Game theory is used to solve the problem of resource allocation. A practical approximated solution with the following two steps is proposed. First, each participant solves its optimal problem independently, without consideration of the multiplexing of resource assignments. A Binary Integer Programming method is proposed to solve the independent optimization. Second, an evolutionary mechanism is designed, which changes multiplexed strategies of the initial optimal solutions of different participants with minimizing their efficiency losses. The algorithms in the evolutionary mechanism take both optimization and fairness into account. It is demonstrated that Nash equilibrium always exists if the resource allocation game has feasible solutions.