Distributed Joint Offloading Decision and Resource Allocation for Multi-User Mobile Edge Computing: A Game Theory Approach

05/06/2018 ∙ by Ning Li, et al. ∙ 0

Due to the spectrum reuse in small cell network, the inter-cell interference has great effect on MEC's performance. In this paper, for reducing the energy consumption and latency of MEC, we propose a game theory based jointing offloading decision and resource allocation algorithm for multi-user MEC. In this algorithm, the transmission power, offloading decision, and mobile user's CPU capability are determined jointly. We prove that this game is an exact potential game and the NE of this game exists and is unique. For reaching the NE, the best response dynamic is applied. We calculate the best responses of these three variables. Moreover, we investigate the properties of this algorithm, including the convergence, the computation complexity, and the price of anarchy. The theoretical analysis shows that the inter-cell interference has great effect on the performance of MEC. The NE of this game is Pareto efficiency and also the global optimal solution of the proposed optimal issue. Finally, we evaluate the performance of this algorithm by simulation. The simulation results illustrates that this algorithm is effective on improving the performance of the multi-user MEC system.



There are no comments yet.


page 1

page 2

page 3

page 4

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.