An Energy-Efficient Collaborative Offloading Scheme With Heterogeneous Tasks for Satellite Edge Computing

Abstract

Satellite edge computing (SEC) can offer task computing services to ground users, particularly in areas lacking terrestrial network coverage. Nevertheless, given the limited energy of low earth orbit (LEO) satellites, they cannot be used to process numerous computational tasks. Furthermore, most existing task offloading methods are designed for homogeneous tasks, which obviously cannot meet service requirements of various computational tasks. In this work, we investigate energy-efficient collaborative offloading scheme with heterogeneous tasks for SEC to save energy and improve efficiency. Firstly, by dividing computational tasks into delay-sensitive (DS) and delay-tolerant (DT) tasks, we propose a collaborative service architecture with ground edge, satellite edge, and cloud, where specific task offloading schemes are given for both sparse and dense user scenarios to reduce the energy consumption of LEO satellites. Secondly, to reduce the delay and failure rate of DS tasks, we propose an access threshold strategy for DS tasks to control the queue length and facilitate load balancing among multiple computing platforms. Thirdly, to evaluate the proposed offloading scheme, we develop the continuous-time Markov chain (CTMC) to model the traffic load on computing platforms, and the stationary distribution is solved employing the matrix-geometric method. Finally, numerical results for SEC are presented to validate the effectiveness of the proposed offloading scheme.