Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario
Aiming at the offloading requirements of ground users'computing tasks in edge computing scenario of low earth orbit(LEO)satellites,a joint offloading and resource allocation optimization(JORAO)algorithm was proposed.Considering the limited coverage time of LEO satellites,the offloading strategy,the allocation of communication and computing resources of LEO satellites were jointly optimized to minimize the average service delay of all ground users.The joint optimization problem of task offloading and resource allocation was decomposed into offloading decision and resource allocation sub-problems,and an alternating optimization method was used to obtain the suboptimal solution of the original optimization problem.The task offloading decision sub-problem was modeled as a coalition game model,and when the game reached Nash equilibrium,the ground user offloading strategy that minimized the system delay was obtained.For the resource allocation sub-problem,the Lagrange multiplier method was used to obtain the optimal band-width and compute resource allocation results.Moreover,the convergence and stability of the proposed algorithm were also demonstrated.The simulation results show that the proposed algorithm has excellent convergence and can signifi-cantly reduce the average service delay of ground users,as well as improve the task offloading success rate.
low earth orbit satelliteedge computingoffloadingresource allocationcoalition game
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