Joint Wireless and Computing Resources Allocation in Multi-Cell MEC

TL;DR

This paper investigates joint wireless and computing resource allocation in multi-cell MEC systems, proposing an iterative method to optimize energy use under response time constraints, highlighting the importance of access point selection.

Contribution

It introduces an iterative resource allocation algorithm for non-convex optimization in multi-cell MEC, considering multiple access points and servers, and evaluates its performance against bounds.

Findings

Access point selection significantly impacts system performance.

The proposed algorithm converges to a local optimum.

Joint resource allocation improves energy efficiency.

Abstract

This paper addresses join wireless and computing resource allocation in mobile edge computing (MEC) systems with several access points and with the possibility that users connect to many access points, and utilize the computation capability of many servers at the same time. The problem of sum transmission energy minimization under response time constraints is considered. It is proved, that the optimization problem is non-convex. The complexity of optimization of a part of the system parameters is investigated, and based on these results an Iterative Resource Allocation procedure is proposed, that converges to a local optimum. The performance of the joint resource allocation is evaluated by comparing it to lower and upper bounds defined by less or more flexible multi-cell MEC architectures. The results show that the free selection of the access point is crucial for good system performance.