Distributed Computation Offloading Based on Stochastic Game in Multi-server Mobile Edge Computing Networks
Shuang Chen, Xin Chen, Ying Chen, Zhuo Li · 2019
With the popularity of the Internet of things (IoT), 5G technology needs to meet various requirements of a large number of IoT applications. Mobile edge computing (MEC) is a promising approach in 5G scenario, which can solve the problems of resource shortage and high latency. Computation offloading is a key technology to reduce latency and energy consumption in MEC. In this paper, we consider a scenario with a dense distribution of edge nodes, namely multi-edge server distribution, and focus on the offloading problem in the overlapping coverage area of service scope. We build a two-step game model using the stochastic game theory. We pay attention to the relevance of state transition, that is, the cost of the next state is taken into account when making decisions in current state. In addition, we prove the existence of Nash Equilibrium (NE) by the concept of exact potential game, then propose the best response based on stochastic game (BRSG) algorithm to solve the problem. Numerical results illustrate that our algorithm can reach a NE through finite number of iterations, and an equilibrium strategy can be obtained. Besides, considering the state correlation makes the equilibrium cost significantly lower.