Probabilistic Fault Diagnosis of Clustered Faults for Multiprocessor Systems

被引：0

作者：

Sun, Xue-Li ^{[1
,2
]}

Fan, Jian-Xi ^{[1
,2
]}

Cheng, Bao-Lei ^{[1
]}

Wang, Yan ^{[1
]}

Zhang, Li ^{[1
]}

机构：

[1] Soochow Univ, Sch Comp Sci & Technol, Suzhou 215006, Peoples R China

[2] Soochow Univ, Prov Key Lab Comp Informat Proc Technol, Suzhou 215006, Peoples R China

来源：

JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY | 2023年 / 38卷 / 04期

基金：

中国国家自然科学基金;

关键词：

regular graph; clustered fault; probabilistic diagnosis algorithm; Preparata Metze Chien model (PMC model); EXTRA CONDITIONAL DIAGNOSABILITY; PARALLEL COMPUTERS; CONNECTIVITY; MODEL;

D O I：

10.1007/s11390-021-1099-0

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

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.

引用

页码：821 / 833

页数：13

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