Energy Efficient Relay Selection and Resource Allocation in D2D-Enabled Mobile Edge Computing

Abstract

In order to improve resource utilization and network capacity, we propose the Device-to-Device (D2D) enabled Mobile Edge Computing (MEC) system, where multiple Smart Devices (SDs) transmit the offloading data to the MEC server with the help of wireless access point (WAP) selected from multiple WAPs. The SD uses the chosen WAP as the communication relay between the MEC server and itself. Aimed to minimize the total energy consumption of the system and satisfy the SDs demand on delay, we jointly optimize relay selection and resource allocation in D2D-enabled MEC system. The problem is formulated as an integer-mixed non-convex optimization problem which is a NP-hard problem. We thus propose a two-phase optimization algorithm that jointly optimizes relay selection policy and resource allocation strategy. In first phase, the original problem is converted into a convex optimization problem by using convex optimization techniques, and the optimal relay selection policy can be achieved by solving the relay selection problem. After obtaining the relay selection policy, the original problem is transformed into a resource allocation problem solved by leveraging the Lagrange Method in the second phase. Furthermore, the proposed algorithm is a low-complexity algorithm which is associated with the root finding method. The optimal relay selection policy and resource allocation strategy can be found in polynomial time. The extensive simulation results are provided to indicate that the D2D-enabled MEC system achieves remarkable results in energy saving. Compared with other baseline methods, our proposed algorithm can not only achieve the optimal solution with less time cost, but also improve the energy efficiency and network capacity.