Dynamic game based task offloading and resource pricing in LEO-multi-access edge computing

Driven by the demand for ubiquitous connection in the Internet of everything era, this paper introduces a new low earth orbit (LEO) satellite-based multi-access edge computing fusion architecture. The architecture regards LEO satellites deployed with high-performance edge modules as superior nodes, which can provide onboard processing mode edge task offloading service for users in complex regions. At the same time, the superior node also has the offloading decision and can offload some edge user tasks to the edge service center in the ground network. Based on differential game theory, we propose a two-stage computing resource purchase strategy and task-offloading resource pricing strategy to ensure the minimum cost of edge computing services for edge users and the maximum benefit for edge service providers and prove the existence of a unique Nash equilibrium solution using Piccard theorem. An algorithm based on the Runge–Kutta method is designed to solve Nash equilibrium, and the simulation results show the effectiveness of the proposed method.