Recovery Routing Based on Q-Learning for Satellite Network Faults - Rentao Gu; Jiawen Qin; Tao Dong; Jie Yin; Zhihui Liu (Complexity)
With the fierce research on the space and terrestrial network, the satellite network as the main component has received increasing attention. Due to its special operating environment, there are temporary link failures caused by interference and permanent port failures caused by equipment problems. In this paper, we propose a new satellite network routing technology for fault recovery based on fault detection. Based on Bayesian decision, this technology judges the probability of each fault by a priori probability of the two faults to achieve the purpose of effectively distinguishing between two types of faults and locate faulty links and node ports. Then, corresponding to the previous two stages of the fault detection, different stages and different methods are updated for different types of fault. We also combine satellite network data from satellite simulation software to validate our study. The results show that the recovery strategy has good performance, and the effective resource utilization rate is improved significantly.