Energy-Efficient Resource Allocation for Relay-Assisted Mobile Edge Computing Systems

Abstract

To meet the requirements of computation intensive and latency sensitive applications, mobile edge computing (MEC) is utilized to improve quality of service, which allows user equipments (UEs) to offload urgent tasks to adjacent edge base stations (BSs) for efficient data processing. Considering the deterioration of wireless channels caused by user mobility and obstacles, this paper investigates a relay-assisted MEC system, where a relay is deployed between UE and BS with better channel condition. UE has three modes for data computing, i.e., local computing, relay-assisted offloading, and direct transmission offloading. With the aim of energy consumption minimization, an iterative and low-complexity algorithm is proposed by jointly optimizing task partition, local CPU frequency, bandwidth allocation, and power control at both UE and relay, and the closed-form optimal solutions are derived. Numerical results validate that the designed algorithm outperforms static and fractional power control schemes, and the relay-assisted MEC system can significantly decrease energy consumption in comparison with that without the assistance of relay.