Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing

TLDR

Mobile edge computing and in‑network caching are emerging paradigms that enhance device computation and manage traffic, but key challenges remain in computation offloading and content caching strategies. The study aims to jointly address computation offloading and content caching in wireless cellular networks by formulating a revenue‑maximizing optimization problem. The authors transform the problem into a convex form, decompose it for distributed solution, and implement an ADMM‑based algorithm for efficient optimization. Simulations confirm the scheme’s effectiveness across varied system parameters.

Abstract

Mobile edge computing has risen as a promising technology for augmenting the computational capabilities of mobile devices. Meanwhile, in-network caching has become a natural trend of the solution of handling exponentially increasing Internet traffic. The important issues in these two networking paradigms are computation offloading and content caching strategies, respectively. In order to jointly tackle these issues in wireless cellular networks with mobile edge computing, we formulate the computation offloading decision, resource allocation and content caching strategy as an optimization problem, considering the total revenue of the network. Furthermore, we transform the original problem into a convex problem and then decompose it in order to solve it in a distributed and efficient way. Finally, with recent advances in distributed convex optimization, we develop an alternating direction method of multipliers-based algorithm to solve the optimization problem. The effectiveness of the proposed scheme is demonstrated by simulation results with different system parameters.