Adaptive Snapshot Routing Based on Space Debris Risk Perception in Satellite Optical Networks

With the advantages of large transmission capacity, high data rate and good confidentiality, inter-satellite laser communication has become a promising alternative for satellite networks. However, with more and more satellite nodes being launched into the space, the number of space debris will increase rapidly. Due to the nature of linear transmission of laser links, space debris may cause the uncertain interruption of laser links, and further degrade the link survivability of satellite optical networks. In this paper, we design a risk perception model based on machine learning for inter-satellite laser links risk caused by space debris. Based on this model, we propose an adaptive snapshot routing strategy based on flexible granularity (ASRS-FG), which can effectively avoid the risk of inter satellite link interruption caused by space debris. Finally, to verify the performance of the algorithm, we built a satellite optical networks simulation platform. The simulation results show that our model’s prediction accuracy on space debris risk reaches 95%. Compared with the equal-length snapshot routing strategy (ESRS), ASRS-FG effectively avoids the use of risky laser links and achieves higher service success ratio and fewer snapshot switching times.