Non-cooperative game algorithms for computation offloading in mobile edge computing environments

Abstract

Mobile Edge Computing (MEC) has become a promising technology for 5G networks. Computation offloading is an essential issue of MEC, which enables mobile User Equipment (UE) to enjoy rich wireless resources and huge computing power anywhere. This paper considers the Quality-of-Experience (QoE) of UEs in 5G MEC systems and presents a dynamic non-cooperative game (QCOG-DG) algorithm and a static non-cooperative game (QCOG-SG) algorithm for computation offloading of MEC applications. We establish an MEC computation offloading model by considering the QoE requirements of UEs, and discuss the communication overheads, computation cost, and energy consumption models to minimize the energy consumption and time delay of each UE. Considering that there are multiple UEs who want to offload their computation tasks to a resource-constrained MEC server, and each UE is selfish and competitive, we formulate the problem of computation offloading decision as a non-cooperative game model. We prove the existence of a Nash Equilibrium (NE) solution for the proposed game model. In addition, we propose an algorithm that jointly optimizes energy consumption and time delay under QoE preferences to achieve optimal offloading benefits for each UE. Moreover, we respectively propose a dynamic non-cooperative game (QCOG-DG) algorithm and a static non-cooperative game (QCOG-SG) algorithm to efficiently find the NE solution. Extensive simulation experiments are conducted to verify the effectiveness of the proposed MEC computation offloading model and the QCOG-DG and QCOG-SG algorithms. Simulation results show that the proposed QCOG-DG algorithm can efficiently find the NE solutions in the MEC scenarios with UEs of different sizes.