Resource Allocation in a Relay-Aided Mobile Edge Computing System

Mobile edge computing (MEC) provides wireless devices (WDs) more computing capability and lower latency by allowing them to offload their computation tasks to a nearby more powerful server. Furthermore, adopting the relaying technique can effectively improve the offloading performance, especially when the wireless channel conditions between WD and MEC server are poor. In this article, we consider a multiuser relay-aided MEC system targeting at minimizing the energy consumption. The relay can either execute the computation task by itself or offload the task to the MEC server. Under the partial computation offloading mode, an energy minimization problem is investigated by jointly optimizing transmit power, offloading time duration, and central processing unit (CPU) frequencies. To solve the nonconvex optimization problem, an iterative algorithm based on successive convex approximation (SCA) is developed. Furthermore, the closed-form expressions for the optimal transmission powers and the CPU frequencies are derived. The simulation results show that the proposed scheme can achieve a lower energy consumption than other benchmark schemes.

Automated summary

Mobile edge computing (MEC) enables wireless devices to offload computation tasks to powerful servers, providing them with more computing capability and lower latency. The relaying technique improves offloading performance, especially in poor channel conditions. This article focuses on a multiuser relay-aided MEC system that aims to minimize energy consumption. Using an iterative algorithm based on successive convex approximation (SCA), the problem of energy minimization is solved by jointly optimizing transmit power, offloading time duration, and CPU frequencies.