Fair Resource Allocation for System Throughput Maximization in Mobile Edge Computing

Abstract

Communication resource allocation is important for improving the performance of users in mobile edge computing (MEC) scenarios. In existing studies, the users in the MEC system typically suffer from unfair resource allocation, which results in the inefficient resource utilization and degraded user performance. To address this challenge, in this paper we propose a fair resource allocation approach to maximize the overall network throughput, under the constraint of each mobile user's minimum transmission rate. We formulate the problem as a fair Nash bargaining resource allocation game, and the existence and uniqueness of the solution to this game model are analyzed. By adopting the time-sharing variable, we obtain the near optimal bargaining resource allocation strategy for the mixed integer nonlinear programming optimization. The user's priority is further considered in the iterative implementation of the proposed algorithm by considering the time delay constraint of users. Simulation results show that the proposed scheme outperforms existing methods in terms of resource allocation fairness and overall system throughput.