Game Theory Based Task Offloading, Content Caching and Resource Pricing under Edge-Cloud Collaboration in 6G Network

Abstract

With the popularity of computation-intensive applications, tremendous computing pressure has been placed on the network edges. In order to effectively mitigate the computing pressure on network edges, an edge-cloud cooperative scheme is proposed. We consider mobile devices (MDs) can offload computation tasks to base stations (BSs) and cache content on cloud server (CS). Meanwhile, the overloaded BSs can offload tasks to CS for processing. CS and BSs are required to price their own resources or services, such as computing resources, storage resources, and computing services. Taking into account the economic factor, delay constraint and energy consumption cost, the problem of task offloading, content caching and resource pricing are jointly optimized to maximize the utility of all participants in the network. The three-stage Stackelberg game is established to investigate the interaction among CS, BSs and MDs. The existence of Stackelberg equilibrium (SE) is proved in three stages. Additionally, the Three-stage Equilibrium strategy algorithm based on Backward Induction (TEBI) is proposed to obtain the equilibrium strategies. The experimental results illustrate that TEBI algorithm can reach SE and converge rapidly, the cooperation pattern can shorten the task processing delay and improve the utility of participants.