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Optimal association of mobile users to multi-access edge computing resources

机译：移动用户到多访问边缘计算资源的最佳关联

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Multi-access edge computing (MEC) plays a key role in fifth-generation (5G) networks in bringing cloud functionalities at the edge of the radio access network, in close proximity to mobile users. In this paper we focus on mobile-edge computation offloading, a way to transfer heavy demanding, and latency-critical applications from mobile handsets to close-located MEC servers, in order to reduce latency and/or energy consumption. Our goal is to provide an optimal strategy to associate mobile users to access points (AP) and MEC hosts, while contextually optimizing the allocation of radio and computational resources to each user, with the objective of minimizing the overall user transmit power under latency constraints incorporating both communication and computation times. The overall problem is a mixed-binary problem. To overcome its inherent computational complexity, we propose two alternative strategies: i) a method based on successive convex approximation (SCA) techniques, proven to converge to local optimal solutions; ii) an approach hinging on matching theory, based on formulating the assignment problem as a matching game.
机译：多接入边缘计算（MEC）在第五代（5G）网络中扮演了在无线电接入网络边缘的云功能，密切接近移动用户的关键作用。在本文中，我们专注于移动边缘计算卸载，一种从移动手机到靠近MEC服务器的重大要求苛刻和延迟关键的应用程序，以减少延迟和/或能量消耗。我们的目标是提供一个最佳的策略来将移动用户与访问点（AP）和MEC主机相关联，同时上下文地优化对每个用户的无线电和计算资源的分配，其目的是最小化延迟约束下的整体用户发送功率通信和计算时间。整体问题是混合二进制问题。为了克服其固有的计算复杂性，我们提出了两种替代策略：i）一种基于连续凸近似（SCA）技术的方法，证明可以收敛到本地最佳解决方案; ii）基于将分配问题作为匹配游戏的匹配问题铰接对匹配理论的方法。

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