Probabilistic Fault Diagnosis of Clustered Faults for Multiprocessor Systems

被引:0
|
作者
Xue-Li Sun
Jian-Xi Fan
Bao-Lei Cheng
Yan Wang
Li Zhang
机构
[1] Soochow University,School of Computer Science and Technology
[2] Soochow University,Provincial Key Laboratory for Computer Information Processing Technology
关键词
regular graph; clustered fault; probabilistic diagnosis algorithm; Preparata Metze Chien model (PMC model);
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中图分类号
学科分类号
摘要
With the development of high-performance computing and the expansion of large-scale multiprocessor systems, it is significant to study the reliability of systems. Probabilistic fault diagnosis is of practical value to the reliability analysis of multiprocessor systems. In this paper, we design a linear time diagnosis algorithm with the multiprocessor system whose threshold is set to 3, where the probability that any node is correctly diagnosed in the discrete state can be calculated. Furthermore, we give the probabilities that all nodes of a d-regular and d-connected graph can be correctly diagnosed in the continuous state under the Weibull fault distribution and the Chi-square fault distribution. We prove that they approach to 1, which implies that our diagnosis algorithm can correctly diagnose almost all nodes of the graph.
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页码:821 / 833
页数:12
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