A fault detection design for clustered space information network based on FTA

Sun, Yuanyuan; Wang, Yongming; Guo, Lili; Ma, Zhong‐Qi; Wang, Huiping

doi:10.1109/iccsnt.2017.8343725

Cited by 1 publication

(1 citation statement)

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“…As the backbone network of the space and terrestrial network, the timely detection and restoration of communication capabilities of satellite network faults ensure the healthy and stable operation of the network. Due to the characteristics of satellite network, such as precious resources and strong dynamics, Sun et al propose a fault detection algorithm combining FTA (Fault Tree Analysis) and cluster method [10], which applies to LEO/MEO/GEO and ground stations. First, the space network is clustered to form a number of management domains.…”

Section: Related Workmentioning

confidence: 99%

Recovery Routing Based on Q-Learning for Satellite Network Faults

Qin

Dong³

et al. 2020

Complexity

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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.

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Section: Related Workmentioning

confidence: 99%