A Hierarchical Game for Joint Wireless and Cloud Resource Allocation in Mobile Edge Computing System
Zhuorui Lan, Weiwei Xia, Wenqing Cui, Feng Yan, Fei Shen, Xuzhou Zuo, Lianfeng Shen · 2018
In this paper, a game theoretic approach is proposed for the joint wireless and cloud resource allocation problem in Mobile Edge Computing (MEC) system. We put forward a hierarchical game based algorithm (HGBA) to address the problem, which includes the lower-level evolutionary game (LEG) and the upper-level exact potential game (UEPG) to jointly allocate wireless and cloud resources for mobile users, aiming at minimizing the cost of mobile terminals (MTs) and maximizing the utility of MEC servers. The existence of Nash equilibrium (NE) is proved. At the lower-level, the dynamic replicator method is applied to obtain the NE so as to minimize the cost of MTs, including momentary cost, energy consumption and delay cost. At the upper-level, to solve the resource sharing problem, we use the convex optimization method and game theory to maximize the servers' utility under MTs' QoE constraints, and NE is obtained through solving Karush-Kuhn-Tucker (KKT) condition. The simulation results show that the average utility of MEC servers is higher compared with existing algorithms, and the cost of MTs is significantly lower than other algorithms with the increasing size of input data.