Abstract
In order to solve the problem of low accuracy of fault diagnosis algorithms in multiple management domain environments such as such as Software Defined Networks (SDN), this paper proposes a multi-domain cooperative service fault diagnosis algorithm under network slice based on the correlation between faults and symptoms. According to the relationship between the management domain and the symptoms, the network resources corresponding to the symptoms are divided into resources within the management domain and inter-domain resources. When constructing a suspected fault set, the suspected fault set is constructed according to the number of simultaneous faults, and the final suspected fault set is determined by calculating the interpretation capability of the suspected fault. Finally, according to Bayesian theory, the fault set with the highest probability is regarded as the most probable fault set. Compared with the existing classical algorithms in the experimental part, it is verified that the algorithm in this paper improves the accuracy of fault diagnosis and reduces the false alarm rate of fault diagnosis.
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Acknowledgement
This work is supported by science and technology project from State Grid Jiangsu Electric Power Co., Ltd: “Technology Research for High-efficiency and Intelligent Cooperative Wide-area Power Data Communication Networks (SGJSXT00DDJS1900168)”.
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Li, W., Dai, Y., Xu, Y., Wu, X., Li, W., Lin, P. (2021). Multi-domain Cooperative Service Fault Diagnosis Algorithm Under Network Slicing with Software Defined Networks. In: Cheng, M., Yu, P., Hong, Y., Jia, H. (eds) Smart Grid and Innovative Frontiers in Telecommunications. SmartGIFT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 373. Springer, Cham. https://doi.org/10.1007/978-3-030-73562-3_5
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DOI: https://doi.org/10.1007/978-3-030-73562-3_5
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