HIQCO: A Hierarchical Optimization Method for Computation Offloading and Resource Optimization in Multi-Cell Mobile-Edge Computing Systems

Mobile-Edge Computing (MEC) addresses the shortcomings of mobile devices in terms of computing performance and energy efficiency by offloading computation tasks to the edge of the network. In this paper, a multi-cell MEC system is considered, where each small cell connects to a common MEC server, and the problem of minimizing system overhead in the MEC system is solved by jointly optimizing the computation offloading decisions, communication and computational resources. This problem is a mixed integer nonlinear programming problem (MINLP). Owning to the combined nature and complexity of this problem, we adopt a method to transform the original problem into two sub-problems: (i) joint optimization computation offloading decision and channel assignment problem (JO-CODCA) and (ii) joint optimization transmission power and computational resource allocation problem (JO-TPCRA). For the transformed sub-problems, we propose a hierarchical optimization method (HIQCO) that combines immune algorithm (IA), quasi-convex optimization and convex optimization techniques. Experimental results show that the proposed HIQCO give better performance comparing with the other compared algorithms in terms of system overhead.