改进BARINEL算法的网络时延故障诊断方法

随着网络系统的规模和复杂性不断增加，网络系统不可避免地会出现不同类型的故障。本文提出了模糊逻辑扩展的改进BARINEL算法，实现网络延迟软故障诊断。为了解决求解诊断候选项的指数复杂度问题，设计了一种基于启发式函数的最小命中集方法，有效降低了求解中的计算复杂度。针对BARINEL算法对多值逻辑错误检测机制表达能力不足，提出了模糊逻辑的BARINEL算法，能更有效诊断出故障链路及故障点。实验结果表明，当网络中至少有20条可用路径条件下，所提出的新方法能够花费更少的代价正确识别出故障节点。

Network delay fault diagnosis method with improved BARINEL algorithm

With the increasing scale and complexity of network systems, it is inevitable that different types of faults will occur in network systems. In this paper, an improved BARINEL algorithm based on fuzzy logic extension is proposed to realize network delay soft fault diagnosis. In order to solve the exponential complexity problem of solving diagnostic candidates, a minimum hit set method based on heuristic function is designed, which effectively reduces the computational complexity in the solution. Aiming at the insufficient ability of BARINEL algorithm to express multi-valued logic error detection mechanism, a fuzzy logic BARINEL algorithm is proposed, which can diagnose fault links and fault points more effectively. The experimental results show that when there are at least 20 available paths in the network, the proposed method can correctly identify the faulty nodes at a lower cost.