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An Improved Distributed Gradient-Push Algorithm for Bandwidth Resource Allocation over Wireless Local Area Network

Author

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  • Zhengqing Shi

    (Nanjing University of Science and Technology)

  • Chuan Zhou

    (Nanjing University of Science and Technology)

Abstract

Bandwidth allocation problems over wireless local area network have attracted extensive research recently due to the rapid growth in the number of users and bandwidth-intensive applications. In this paper, a bandwidth allocation problem over wireless local area network with directed topologies is investigated and the global objective function of the problem consists of local downloading and uploading cost with both constraints of feasible allocation region and network resources. An improved high-efficiency gradient-push algorithm is proposed for the bandwidth allocation problem which not only guarantees successful data transmission but also minimizes the global objective function. Compared with the existing distributed algorithms, firstly, we use weighted running average bandwidth to replace the current state variables which can ensure the solution converge to the optimal value asymptotically with probability one. Next, noisy gradient samples are used in the proposed algorithm instead of accurate gradient information which enhances the robustness and expands the scope of application. Theoretical analysis shows the convergence rate of the time-averaged value to the optimal solution. Finally, numerical examples are presented to validate the proposed algorithm.

Suggested Citation

  • Zhengqing Shi & Chuan Zhou, 2019. "An Improved Distributed Gradient-Push Algorithm for Bandwidth Resource Allocation over Wireless Local Area Network," Journal of Optimization Theory and Applications, Springer, vol. 183(3), pages 1153-1176, December.
    • Handle: RePEc:spr:joptap:v:183:y:2019:i:3:d:10.1007_s10957-019-01588-7
    DOI: 10.1007/s10957-019-01588-7
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    Cited by:

    1. Chuanye Gu & Lin Jiang & Jueyou Li & Zhiyou Wu, 2023. "Privacy-Preserving Dual Stochastic Push-Sum Algorithm for Distributed Constrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 197(1), pages 22-50, April.

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