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Service Fault Location Algorithm based on Network Characteristics under 5G Network Slicing

机译:基于5G网络切片下网络特性的服务故障定位算法

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In order to solve the problem of long diagnosis time for fault diagnosis algorithms in large-scale environments, this paper proposes a service fault location algorithm based on network characteristics. First, based on the virtual network mapping data, the service is associated with the underlying resources to build a Bayesian fault location model. Second, by analyzing the network topology and the running status of each service, the probability of network node failure is calculated based on the multi-attribute characteristics. Finally, the fault location is achieved by calculating the set of suspected faults with the strongest ability to explain abnormal symptoms. The experimental part compares the algorithm of this paper with the classical algorithm, and verifies that the algorithm of this paper improves the accuracy of fault diagnosis and reduces the time cost of fault diagnosis.
机译:为了解决大规模环境中故障诊断算法的长诊断时间的问题,本文提出了一种基于网络特性的服务故障定位算法。 首先,基于虚拟网络映射数据,该服务与基础资源相关联,以构建贝叶斯故障定位模型。 其次,通过分析每个服务的网络拓扑和运行状态,基于多属性特征来计算网络节点故障的概率。 最后,通过计算具有最强的疑似症状的疑似故障来实现故障位置。 实验部分将本文的算法与经典算法进行比较,并验证本文的算法提高了故障诊断的准确性并降低了故障诊断的时间成本。

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