Energy Minimization for D2D-Assisted Mobile Edge Computing Networks

This paper addresses the energy minimization problem in Device-to-Device (D2D) assisted Mobile Edge Computing (MEC) networks under the latency constraint of each individual task and the computing resource constraint of each computing entity. The energy minimization problem is formed as a two-stage optimization problem. Specifically, in the first stage, an initial feasibility problem is formed to maximize the number of executed tasks and the global energy minimization problem is tackled in the second stage while maintaining the maximum number of executed tasks. Both of the optimization problems in two stages are NP-hard, therefore a low-complexity algorithm is developed for the initial feasibility problem with a supplementary algorithm further proposed for energy minimization. Simulation results demonstrate the near-optimal performance of the proposed algorithms and the fact that with the assistance of D2D communication, the number of executed tasks is greatly increased and the energy consumption per executed task is significantly reduced in MEC networks, especially in dense user scenario.