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Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation

Author

Listed:
  • Shiyong Li

    (Yanshan University)

  • Wei Sun

    (Yanshan University)

  • Huan Liu

    (Yanshan University)

Abstract

Peer-to-peer (P2P) networks support a wide variety of network services including elastic services such as file-sharing and downloading and inelastic services such as real-time multiparty conferencing. Each peer who acquires a service will receive a certain level of satisfaction if the service is provided with a certain amount of resource. The utility function is used to describe the satisfaction of a peer when acquiring a service. In this paper we consider optimal resource allocation for elastic and inelastic services and formulate a utility maximization model which is an intractable and difficult non-convex optimization problem. In order to resolve it, we apply the successive approximation method and approximate the non-convex problem to a serial of equivalent convex optimization problems. Then we develop a gradient-based resource allocation scheme to achieve the optimal solutions of the approximations. After a serial of approximations, the proposed scheme can finally converge to an optimal solution of the primal utility maximization model for resource allocation which satisfies the Karush–Kuhn–Tucker conditions.

Suggested Citation

  • Shiyong Li & Wei Sun & Huan Liu, 2022. "Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation," Operational Research, Springer, vol. 22(3), pages 2605-2630, July.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:3:d:10.1007_s12351-021-00622-9
    DOI: 10.1007/s12351-021-00622-9
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    References listed on IDEAS

    as
    1. Shiyong Li & Yue Zhang & Wei Sun, 2019. "Optimal Resource Allocation Model and Algorithm for Elastic Enterprise Applications Migration to the Cloud," Mathematics, MDPI, vol. 7(10), pages 1-20, October.
    2. Barry R. Marks & Gordon P. Wright, 1978. "Technical Note—A General Inner Approximation Algorithm for Nonconvex Mathematical Programs," Operations Research, INFORMS, vol. 26(4), pages 681-683, August.
    3. Seyedakbar Mostafavi & Mehdi Dehghan, 2017. "A stochastic approximation resource allocation approach for HD live streaming," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(1), pages 87-101, January.
    4. Shiyong Li & Wei Sun, 2016. "A mechanism for resource pricing and fairness in peer-to-peer networks," Electronic Commerce Research, Springer, vol. 16(4), pages 425-451, December.
    5. Farhood Rismanchian & Young Hoon Lee, 2018. "Moment-based approximations for first- and second-order transient performance measures of an unreliable workstation," Operational Research, Springer, vol. 18(1), pages 75-95, April.
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