Cooperative Computing Offloading and Resource Allocation in Distributed Satellite Clusters
In the all-space-based scenario of on-orbit construction and maintenance of distributed clusters,the clusters are highly dynamic,and the tasks of delay-sensitive(class A)and delay-tolerant(class B)are generated concurrently by resource-constrained terminal satellites,while the traditional space-ground cooperative offloading scenario does not consider the satellite dynamics and the diversity of task types.Aiming at the needs of all-space-based scenarios,a distributed star clusters edge computing architecture is constructed,and a differential adaptive reward system-deep deterministic policy gradient(DARS-DDPG)algorithm is proposed.By introducing the differential adaptive reward system into the traditional DDPG algorithm,the algorithm can distinguish the importance of different types of tasks in the learning process and adaptively adjust the penalty coefficients of the two types of tasks.The completion rate of the two types of tasks is the highest.Simulation results show that compared with the baseline strategy and the strategy learned by the traditional DDPG,the strategy learned by DARS-DDPG has a significant improvement in task delay and the completion rate of A and B tasks.
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