A study for inter-satellite cooperative computation offloading in LEO satellite networks

Low Earth orbit (LEO) satellite networks have the advantages of low transmission delay and low deployment cost, playing an important role in providing reliable services to ground users. This paper studies an efficient inter-satellite cooperative computation offloading (ICCO) algorithm for LEO satellite networks. Specifically, an ICCO system model is constructed, which considers using neighboring satellites in the LEO satellite networks to collaboratively process tasks generated by ground user terminals, effectively improving resource utilization efficiency. Additionally, the optimization objective of minimizing the system task computation offloading delay and energy consumption is established, which is decoupled into two sub-problems. In terms of computational resource allocation, the convexity of the problem is proved through theoretical derivation, and the Lagrange multiplier method is used to obtain the optimal solution of computational resources. To deal with the task offloading decision, a dynamic sticky binary particle swarm optimization algorithm is designed to obtain the offloading decision by iteration. Simulation results show that the ICCO algorithm can effectively reduce the delay and energy consumption.