Latency guaranteed joint optimal traffic intelligent scheduling in large-scale satellite networks

Abstract

With the continuous growth of the scale and traffic bearing capacity of satellite networks, it becomes increasingly difficult to ensure the traffic end-to-end latency performance in scheduling processes. Inefficient traffic scheduling methods cannot adapt to the dynamic variations of topology connections and traffic loads of the entire network, which results in the timeout of massive transmissions and the waste of limited satellite network resources. In response to the above issues, we analyze the factors affecting the latency performance at the satellite node level and network level from the perspective of traffic packets. On this basis, we construct a Markov decision process (MDP) based on states including residual latency, residual hops, satellite load, and priority. To deal with large amounts of states and unpredictable state transition probabilities in the MDP, we propose a latency guaranteed joint optimal traffic intelligent scheduling algorithm based on the asynchronous advantage actor–critic. The simulation results show that our method improves the packet successful delivery ratio by at least 20% compared to contrast methods, while satisfying packet end-to-end latency requirements.