AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (130.1 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline

Diagnosability of the Incomplete Star Graphs

Shuxia ZHENGShuming ZHOU( )
Key Laboratory of Network Security and Cryptology, Fujian Normal University, Fuzhou 350007, China
Show Author Information

Abstract

The growing size of the multiprocessor systems increases their vulnerability to component failures. It is crucial to local and to replace the fault processors to maintain system’s high reliability. The fault diagnosis is the process of identifying faulty processors in a system through testing. This paper establishes the diagnosabilities of the incomplete star graph Sn (n≥4) with missing links under the PMC model and its variant, the BGM model, and shows that the diagnosabilities of incomplete star graph Sn under these two diagnostic models can be determined by the minimum degree of its topology structure. This method can also be applied to the other existing multiprocessor systems.

References

【1】
【1】
 
 
Tsinghua Science and Technology
Pages 105-109

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
ZHENG S, ZHOU S. Diagnosability of the Incomplete Star Graphs. Tsinghua Science and Technology, 2007, 12(S1): 105-109. https://doi.org/10.1016/S1007-0214(07)70093-7

7

Views

0

Downloads

0

Crossref

N/A

Web of Science

11

Scopus

0

CSCD

Received: 01 February 2007
Published: 01 July 2007
© Tsinghua University Press 2007