A Game theory-based Computation Offloading Method in Cloud-Edge Computing Networks

In this paper, we propose a computation offloading method based on the game theory, which is suitable for cloud-edge computing networks. We consider that the Cloud Server (CS) can offload the computation tasks to wireless Access Points (APs) associated with Edge Servers (ESs) to accelerate processing. ESs can gain benefits through computation offloading, while the CS can reduce its cost and computing pressure. We model the interaction between the CS and ESs as a Stackelberg game, and use the backward induction method to analyze the proposed game. We prove that the game can achieve a unique Nash equilibrium. Then, we propose a Gradient-based Iterative Search Algorithm (GISA) to maximize the utility of the CS and ESs. Finally, numerical simulation results show that our proposed method greatly outperforms other benchmark schemes under different scenarios, and can encourage ESs to trade their computation resources with the CS effectively.