Game Theory for Computation Offloading and Resource Allocation in Edge Computing: A Survey

Edge computing is considered a promising approach to provide cloud computing capabilities at the edge of the network near to the users. However, the limited number of computation and communication resources at the edge have made the problem of offloading and resource allocation a challenging issue for service providers. Game theory analyzes the behavior of the users and succeeds to obtain solutions in this area where all users are satisfied and the problem reaches an equilibrium state. In this paper, first we give a brief background on game theory showing its definition, types and advantages. Second, we give an overview about edge computing system showing its architecture, challenges and kinds of resource management. Third, we provide a survey about significant achievements of applying game theory in edge computing problems. We categorize the state-of-the-art according to the objective function of the problem. It is divided into seven classes: 1) minimizing the latency, 2) minimizing the energy, 3) minimizing the cost, 4) minimizing both latency and energy, 5) minimizing energy and cost, 6) minimizing latency and cost and finally, 7) minimizing all together latency, cost and energy. Moreover, we present the lessons learned and the future research directions.