Energy-Efficient Parallel Multi-Access Edge Computing in OFDMA Wireless Networks

We study a parallel multi-access edge computing (MEC) system in this work and investigate its energy-efficient resources management. Particularly, the MEC system consists of an edge node and a number of mobile users, where each user has an inelastic computing task with nonnegligible duration of task execution and nonnegligible size of task result. In addition, the MEC system operates in orthogonal frequency division multiple access (OFDMA) wireless networks and can support the transmission as well as the execution of different tasks in parallel. On this basis, we build a nonconvex mixed-integer nonlinear programming (MINLP) problem aiming to minimize the energy consumed by the system. By using the McCormick method and exploring the problem's structural properties, we first equivalently transform it to a manageable convex MINLP problem, and then devise two low-complexity suboptimal algorithms. Finally, numerical results are presented to show the effectiveness of our proposed algorithms.