Abstract
In order to reduce fault location time in data network supporting quantum communication (DNQC), the relationship between faults and symptoms of DNQC is analyzed, and the fault propagation model of DNQC is constructed based on Bayesian theory. Moreover, in order to reduce the complexity of fault location in large-scale fault propagation models, the large-scale fault propagation model is segmented into multiple independent sub-models based on D-segmentation theory. Finally, the maximum likelihood hypothesis is used to solve the suspected fault set for each sub-model. After the fault set is merged and deduplicated, the fault set that can explain all negative symptoms is found according to the correspondence between the fault and the symptom.
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This work is supported by science and technology project of State Grid Corporation headquarters (research on the key technology of quantum secure communication practicalization).
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Xie, K., Zhao, Z., Gao, D., Li, B., Chen, H. (2021). Efficient Fault Location Algorithm Based on D-Segmentation for Data Network Supporting Quantum Communication. In: Liu, Q., Liu, X., Li, L., Zhou, H., Zhao, HH. (eds) Proceedings of the 9th International Conference on Computer Engineering and Networks . Advances in Intelligent Systems and Computing, vol 1143. Springer, Singapore. https://doi.org/10.1007/978-981-15-3753-0_87
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DOI: https://doi.org/10.1007/978-981-15-3753-0_87
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