Energy-Efficient Offloading and Resource Allocation for Multi-Access Edge Computing

Multi-access edge computing (MEC), one of the key technologies of 5G, offloads the computing tasks generated by smart devices to MEC servers. Compared with traditional centralized cloud computing, MEC can significantly reduce the delays in the transmission and data exchange process, and relieve the computational burden of the core network server. In order to minimize the weighted total energy and time consumption under delay requirements, this paper presents a strategy which can offload the computing task from user to MEC server and central cloud server (CCS). Moreover, a priority-based joint calculation offloading algorithm is proposed to figure out the resource allocation problem. In particular, the proposed algorithm sets a priority for each user, and the user with high priority can preferentially select a channel with high transmission quality. The simulation results indicate that the total cost of the proposed algorithm is reduced by 50 percent, compared with the local computing.