Dynamic Spectrum Allocation Enabled Multi-user Latency Minimization in Mobile Edge Computing

Yang Li, Yuan Wu, Weijia Jia
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引用次数: 1

Abstract

Mobile edge computing (MEC) has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for terminal devices. In this paper, we investigate multi-user computation offloading in MEC and propose a joint optimization of offloading decisions, bandwidth and computation-resource allocations, with the objective of minimizing the total latency for completing all users’ tasks. Due to the non-convexity of the formulated joint optimization problem, we identify its layer structure and decompose it into two problems, i.e·, a sub-problem and a top-problem. For the sub-problem, we propose a bisection-search based algorithm to efficiently find the optimal offloading solutions under a given feasible top-problem solution. Then, we use a linear-search based algorithm to obtain the optimal solution of the top-problem. Numerical results are provided to validate our proposed algorithm for minimizing the total latency in MEC-based multi-user computation offloading. We also demonstrate the advantage of our proposed algorithm in comparison with the conventional multi-user computation offloading schemes.
动态频谱分配实现移动边缘计算中的多用户延迟最小化
移动边缘计算(MEC)被设想为一种高效的解决方案,为终端设备提供计算密集型但对延迟敏感的服务。在本文中,我们研究了MEC中的多用户计算卸载,并提出了卸载决策、带宽和计算资源分配的联合优化,目标是最小化完成所有用户任务的总延迟。由于所建立的联合优化问题的非凸性,我们识别了其层结构,并将其分解为两个问题,即子问题和顶问题。对于子问题,我们提出了一种基于二分搜索的算法,在给定可行的顶问题解下有效地找到最优卸载解。然后,我们使用基于线性搜索的算法来获得顶问题的最优解。数值结果验证了该算法在基于mec的多用户计算卸载中最小化总延迟的有效性。与传统的多用户计算卸载方案相比,我们还证明了该算法的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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