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Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform

Author

Listed:
  • Mohammad Mehedi Hassan

    (King Saud University
    Kyung Hee University)

  • M. Shamim Hossain

    (King Saud University)

  • A. M. Jehad Sarkar

    (Hankuk University of Foreign Studies)

  • Eui-Nam Huh

    (Kyung Hee University)

Abstract

Distributed resource allocation is a very important and complex problem in emerging horizontal dynamic cloud federation (HDCF) platforms, where different cloud providers (CPs) collaborate dynamically to gain economies of scale and enlargements of their virtual machine (VM) infrastructure capabilities in order to meet consumer requirements. HDCF platforms differ from the existing vertical supply chain federation (VSCF) models in terms of establishing federation and dynamic pricing. There is a need to develop algorithms that can capture this complexity and easily solve distributed VM resource allocation problem in a HDCF platform. In this paper, we propose a cooperative game-theoretic solution that is mutually beneficial to the CPs. It is shown that in non-cooperative environment, the optimal aggregated benefit received by the CPs is not guaranteed. We study two utility maximizing cooperative resource allocation games in a HDCF environment. We use price-based resource allocation strategy and present both centralized and distributed algorithms to find optimal solutions to these games. Various simulations were carried out to verify the proposed algorithms. The simulation results demonstrate that the algorithms are effective, showing robust performance for resource allocation and requiring minimal computation time.

Suggested Citation

  • Mohammad Mehedi Hassan & M. Shamim Hossain & A. M. Jehad Sarkar & Eui-Nam Huh, 2014. "Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform," Information Systems Frontiers, Springer, vol. 16(4), pages 523-542, September.
    • Handle: RePEc:spr:infosf:v:16:y:2014:i:4:d:10.1007_s10796-012-9357-x
    DOI: 10.1007/s10796-012-9357-x
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    References listed on IDEAS

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    1. Kevin Lai & Lars Rasmusson, 2005. "Tycoon: an Implementation of a Distributed, Market-based Resource Allocation System," Computing in Economics and Finance 2005 6, Society for Computational Economics.
    2. Fontes, Dalila B.M.M. & Hadjiconstantinou, Eleni & Christofides, Nicos, 2006. "A dynamic programming approach for solving single-source uncapacitated concave minimum cost network flow problems," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1205-1219, October.
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    Cited by:

    1. Li Chunlin & Li LaYuan, 2017. "Optimal scheduling across public and private clouds in complex hybrid cloud environment," Information Systems Frontiers, Springer, vol. 19(1), pages 1-12, February.
    2. Jörn Künsemöller & Nan Zhang & Kimmo Berg & João Soares, 2017. "A game-theoretic evaluation of an ISP business model in caching," Information Systems Frontiers, Springer, vol. 19(4), pages 803-818, August.
    3. Sanjaya K. Panda & Indrajeet Gupta & Prasanta K. Jana, 0. "Task scheduling algorithms for multi-cloud systems: allocation-aware approach," Information Systems Frontiers, Springer, vol. 0, pages 1-19.
    4. Jörn Künsemöller & Nan Zhang & Kimmo Berg & João Soares, 0. "A game-theoretic evaluation of an ISP business model in caching," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    5. Shuai Yuan & Sanjukta Das & Ram Ramesh & Chunming Qiao, 2023. "Availability-Aware Virtual Resource Provisioning for Infrastructure Service Agreements in the Cloud," Information Systems Frontiers, Springer, vol. 25(4), pages 1495-1512, August.
    6. Chunlin Li & Yun Chang Liu & Xin Yan, 2017. "Optimization-based resource allocation for software as a service application in cloud computing," Journal of Scheduling, Springer, vol. 20(1), pages 103-113, February.
    7. Sanjaya K. Panda & Indrajeet Gupta & Prasanta K. Jana, 2019. "Task scheduling algorithms for multi-cloud systems: allocation-aware approach," Information Systems Frontiers, Springer, vol. 21(2), pages 241-259, April.

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