Joint Computation Offloading and Resource Allocation for Mobile-Edge Computing Assisted Ultra-Dense Networks
Ya Gao, Haoran Zhang, Fei Yu, Yujie Xia, Yongpeng Shi
Abstract
Mobile-edge computing (MEC), enabling to offload computing tasks on mobile devices towards edge servers, can reduce the terminals cost. However, a single MEC sever usually has limited computing capabilities, which can not meet a large number of terminals' requirements. In this paper, we consider an ultra-dense networks (UDN) scenario where the macro base stations (MBSs) are assisted by MEC severs. In particular, we first construct system model for MEC assisted UDN, and build the system overhead minimization. Next, in order to solve the problem, we transform the problem into three sub-problems, i.e., offloading strategies subproblem, channel assignments subproblem, and power allocation subproblem. Then, employing joint offloading and resource allocation algorithms, we obtain the optimal joint strategy for the MEC assisted UDNs. Finally, simulations are conducted to evaluate the performance of our proposed algorithms. Numerical results show that obtained algorithms can effectively reduce the energy consumption of the system and improve the overall performance of the system.