Task Offloading Strategy in Satellite Edge Computing Based on Matching Game

Abstract

The Low Earth Orbit (LEO) satellite network, serving as a vital complement to the terrestrial backbone network, has emerged as a prospective path for future mobile communication systems, owing to its extensive coverage. In this paper, a three-tier computing architecture catering for application scenarios where ground terminal has limited resources and elevated quality of service (QoS) requisites is presented. The proposed design features vertical collaboration among ground users, LEO satellites, and remote cloud servers, providing collaborative computing task offloading capabilities. We consider the delay and energy consumption of the system, formulated the offloading decision problem as a nonlinear integer programming problem, and then introduced an offloading mechanism that utilizes an improved version of the Gale-Shapley (GS) algorithm and non-cooperative game theory (MGSCO) to approximate the optimal solution under specified constraints. The outcomes of simulations indicate that this strategy can significantly mitigate system delays and energy consumption, in contrast to reference strategies.