The 3-extra conditional diagnosability of balanced hypercubes under MM∗ model

Author(s):  
Lili Li ◽  
Xing Zhang ◽  
Qiang Zhu ◽  
Yiguang Bai
2014 ◽  
Vol 63 (7) ◽  
pp. 1847-1851 ◽  
Author(s):  
Qiang Zhu ◽  
Guodong Guo ◽  
Dajin Wang

2017 ◽  
Vol 12 (5) ◽  
pp. 1221-1234 ◽  
Author(s):  
Shiying Wang ◽  
Zhenhua Wang ◽  
Mujiangshan Wang ◽  
Weiping Han

2017 ◽  
Vol 704 ◽  
pp. 62-73 ◽  
Author(s):  
Aixia Liu ◽  
Shiying Wang ◽  
Jun Yuan ◽  
Jing Li

2012 ◽  
Vol 23 (08) ◽  
pp. 1729-1747 ◽  
Author(s):  
SHUMING ZHOU ◽  
LANXIANG CHEN ◽  
JUN-MING XU

The growing size of the multiprocessor system increases its vulnerability to component failures. It is crucial to locate and replace the faulty processors to maintain a system's high reliability. The fault diagnosis is the process of identifying faulty processors in a system through testing. This paper shows that the largest connected component of the survival graph contains almost all of the remaining vertices in the dual-cube DCn when the number of faulty vertices is up to twice or three times of the traditional connectivity. Based on this fault resiliency, this paper determines that the conditional diagnosability of DCn (n ≥ 3) under the comparison model is 3n − 2, which is about three times of the traditional diagnosability.


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