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A Game-Theoretical Approach for Resource Allocation in Mobile Edge Computing

In mobile edge computing (MEC), the computation resource of edge server is limited. Since the resource could be shared by multiple mobile users, it should be carefully allocated and efficiently utilized. In this paper, we adopt a price-based two-tier Stackelberg game to model an MEC system comprised by a single MEC server and multiple users, for which the computation resource is efficiently allocated. In this model, the MEC server acts as the leader who sets the price of its computation resource, and aims to maximize its revenue through renting this resource. The users play as followers who aim to minimize the weighted summation of the monetary cost and the energy consumption, where the weight is chosen by each user independently based on its monetary budget and the battery capacity. By adopting the iterative optimization, we propose a price-based resource optimization algorithm to achieve the Nash Equilibrium among users and the Stackelberg Equilibrium between the server and the users. Simulation results demonstrate that the proposed algorithm can improve the revenue of the server, and meantime reduce the monetary and energy cost for users.