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Optimal Fairness-Aware Resource Supply and Demand Management for Mobile Edge Computing
IEEE Wireless Communications Letters ( IF 6.3 ) Pub Date : 2020-12-21 , DOI: 10.1109/lwc.2020.3046023
Chongtao Guo , Wei He , Geoffrey Ye Li

This letter focuses on fairness-aware resource management in a multi-user and multi-server mobile edge computing (MEC) network, where the resource supply and demand are jointly considered for resource allocation and task assignment, respectively. In particular, we aim to minimize the maximum task execution latency of all users subject to task and resource constraints. Although the optimization problem includes power, spectrum, hashrate, and task variables and is nonconvex in its primal form, it can be equivalently transformed to a more tractable programming. Then, a low-complexity iteration based algorithm is proposed to find the global optimum of the primal problem since only a convex feasibility problem is tackled in each iteration. Simulation results in typical scenarios show that the proposed resource management strategy can reduce the maximum task execution latency of users by more than 15% comparing with the available baseline approaches.

中文翻译:

移动边缘计算的最佳公平意识资源供需管理

这封信的重点是多用户和多服务器移动边缘计算(MEC)网络中的公平感知资源管理,在该网络中,分别考虑了资源的供应和需求以进行资源分配和任务分配。特别是,我们旨在最大程度地减少所有受任务和资源约束的用户的最大任务执行延迟。尽管优化问题包括幂,频谱,哈希率和任务变量,并且在其原始形式上是非凸的,但它可以等效地转换为更易于处理的编程。然后,提出了一种基于低复杂度迭代的算法来寻找原始问题的全局最优解,因为在每次迭代中都只解决了凸的可行性问题。
更新日期:2020-12-21
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