Joint Offloading and Resource Allocation Optimization for Mobile Edge Computing

In this paper, we propose a game theoretic approach for joint offloading and resource allocation optimization (JORAO) problem in mobile edge computing (MEC) system. This study not only investigates offloading strategy, but also considers cloud and wireless resource allocation. Specially, the concern of the JORAO problem is to minimize the energy consumption and monetary cost from mobile terminals' perspective. However, the JORAO problem is non-convex and NP hard. Therefore, it is formulated as a JORAO game. The existence of Nash equilibrium (NE) is proved for it. To obtain NE, we also concentrate on cloud and wireless resource allocation algorithm (CWRAA), which is the sub-algorithm of the JORAO game. For the CWRAA, on one hand, we take consideration of OFDM sub-channels allocation and uplink power allocation in radio access networks (RAN). On the other hand, the computation resource allocation in MEC is studied. Simulation results show that the distributed JORAO game algorithm can nearly minimize the total cost of all mobile terminals (MTs) with low complexity. In addition, the energy consumption and completion time are less when the size of data becomes larger compared with existing algorithms.