QoS-Aware Computation Offloading in LEO Satellite Edge Computing for IoT: A Game-Theoretical Approach

Abstract

Low earth orbit (LEO) satellite edge computing can overcome communication difficulties in harsh environments, which lack the support of terrestrial communication infrastructure. It is an indispensable option for achieving worldwide wireless communication coverage in the future. To improve the quality-of-service (QoS) for Internet-of-things (IoT) devices, we combine LEO satellite edge computing and ground communication systems to provide network services for IoT devices in harsh environments. We study the QoS-aware computation offloading (QCO) problem for IoT devices in LEO satellite edge computing. Then we investigate the computation offloading strategy for IoT devices that can minimize the total QoS cost of all devices while satisfying multiple constraints, such as the computing resource constraint, delay constraint, and energy consumption constraint. We formulate the QoS-aware computation offloading problem as a game model named QCO game based on the non-cooperative competition game among IoT devices. We analyze the finite improvement property of the QCO game and prove that there is a Nash equilibrium for the QCO game. We propose a distributed QoS-aware computation offloading (DQCO) algorithm for the QCO game. Experimental results show that the DQCO algorithm can effectively reduce the total QoS cost of IoT devices.