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Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction

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  • Amin Nezarat
  • GH Dastghaibifard

Abstract

One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer’s utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.

Suggested Citation

  • Amin Nezarat & GH Dastghaibifard, 2015. "Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-29, October.
  • Handle: RePEc:plo:pone00:0138424
    DOI: 10.1371/journal.pone.0138424
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    References listed on IDEAS

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    1. Shuai Ding & Chen-Yi Xia & Kai-Le Zhou & Shan-Lin Yang & Jennifer S Shang, 2014. "Decision Support for Personalized Cloud Service Selection through Multi-Attribute Trustworthiness Evaluation," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-11, June.
    2. Ding, Shuai & Wang, Juan & Ruan, Sumei & Xia, Chengyi, 2015. "Inferring to individual diversity promotes the cooperation in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 71(C), pages 91-99.
    3. Rajiv T. Maheswaran & Tamer Başar, 2003. "Nash Equilibrium and Decentralized Negotiation in Auctioning Divisible Resources," Group Decision and Negotiation, Springer, vol. 12(5), pages 361-395, September.
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    Cited by:

    1. Masih Fadaki & Babak Abbasi & Prem Chhetri, 2022. "Quantum game approach for capacity allocation decisions under strategic reasoning," Computational Management Science, Springer, vol. 19(3), pages 491-512, July.

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