Time-Expanded Graph-Based Dispersed Computing Policy for LEO Space Satellite Computing

Low earth orbit (LEO) satellite network has the advantages of comprehensive coverage and has the unique benefits of short satellite-to-ground transmission distance and low construction cost, which can effectively complement the limited coverage of ground mobile communication network. Hence, LEO satellites gain extensive attention in the field of mobile communication. However, restricted by the existing mode (BP, Bent Pipe) of high transmission latency problems in the LEO space satellite computing (LSSC), it is challenging to meet the low latency requirement of time-sensitive tasks. Therefore, on-orbit collaborative computing technology for LSSC is proposed in this paper. While due to the high dynamic and non-centrality of the LEO satellite system, collaborative computing in satellite networks will face many difficulties. Aiming at the high dynamic and non-centrality of the LEO satellite network, this paper proposes a dispersed computing paradigm for the LEO satellite network, which is suitable for high dynamic no-center scenarios. In this dispersed computing paradigm, a steady-state matrix based on the time-expanded graph (TEG) model is introduced in this paper to steady-state the topology of a high dynamic LEO satellite network. According to the matrix, a transmission capacity and computing capacity based diffusion algorithm (TCGDA) is proposed to perform optimal task allocation in the LEO satellite network. The simulation results show that the proposed dispersed computing method can effectively complete the computing task with the optimized latency.