Multi cell Collaborative Caching Based on Game Theory in Mobile Edge Computing
Mobile edge computing cache and computing services are pushed to the edge network closer to user, separating network data from the remote cloud network to provide better service to users. At present, most of the researches on edge computing barely consider cooperation between the cells. In order to study the benefits brought by the cooperation between multiple cells, this paper proposes a multi cell cellular network model developed as a Stackelberg game problem for the multi cell cache optimization problem. The cell control center and the base station groups are regarded as the dominant and follower of the game model, respectively, and their respective revenue functions are formulated. Because their income function is non continuous function, the traditional game theory solution can't be used to obtain the Nash equilibrium solution. This paper proposes an iterative alternating algorithm to solve the problem. The control center and the base station group respectively use the improved hybrid frog hopping algorithm (SMSA) and the greedy exchange algorithm (GSA) to solve the problem, and the two alternately iterate and finally obtain the approximate solution of the optimal solution of the model. Through numerical simulation experiments, we verify that the proposed algorithm outperforms the greedy algorithm proposed by other researches.