Dynamic Spectrum Sharing for Load Balancing in Multi-Cell Mobile Edge Computing

TL;DR

This paper proposes a distributed, hierarchical approach for dynamic spectrum sharing and resource allocation in large-scale mobile edge computing systems, improving load balancing and resource utilization.

Contribution

It introduces a convex optimization framework and a distributed solution for joint wireless and computing resource allocation in MEC networks.

Findings

Outperforms baseline algorithms in resource allocation efficiency

Effective load balancing through dynamic spectrum sharing

Limited information exchange suffices for near-optimal performance

Abstract

Large-scale mobile edge computing (MEC) systems require scalable solutions to allocate communication and computing resources to the users. In this letter we address this challenge by applying dynamic spectrum sharing among the base stations (BSs), together with local resource allocation in the cells. We show that the network-wide resource allocation can be transformed into a convex optimization problem, and propose a distributed, hierarchical solution with limited information exchange among the BSs. Numerical results demonstrate that the proposed solution is superior to other baseline algorithms, when wireless and computing resource allocation is not jointly optimized, or the wireless resources allocated to the BSs are fixed.