Performance evaluation on hybrid fault diagnosability of regular networks

Guanqin Lian, Shuming Zhou, Sun-Yuan Hsieh, Jiafei Liu, Gaolin Chen, Yihong Wang

Research output: Contribution to journalArticle

Abstract

Diagnosability is an important metric to the capability of fault identification for multiprocessor systems. However, most researches on diagnosability focus on vertex fault. In real circumstances, not only vertex faults take place but also edge malfunctions may arise. Recently, a kind of new diagnosability under hybrid fault circumstances, called h-edge tolerable diagnosability, has been proposed and the h-edge tolerable diagnosability of n-dimensional hypercube under the PMC model and MM model is determined to be n−h for n≥4 and 1≤h≤n−1. In this work, we propose a general approach to determine the h-edge tolerable diagnosability of general regular networks. We show that the h-edge tolerable diagnosability of a t-regular t-connected network with N processors under the PMC model (resp., MM model) is t−h for t≥2 and 1≤h≤t−1 if N≥2(t−h)+1 (resp., N≥2(t−h)+3). Moreover, if G=(V,E) is a t-regular t-diagnosable network under the PMC (resp., MM) model (where t≥2), then th e(G)=t−h for 1≤h≤t−1 under the PMC (resp., MM) model.

Original languageEnglish
Pages (from-to)147-153
Number of pages7
JournalTheoretical Computer Science
Volume796
DOIs
Publication statusPublished - 2019 Dec 3

Fingerprint

Diagnosability
Performance Evaluation
Fault
Model
Fault Identification
Multiprocessor Systems
Vertex of a graph
Hypercube
n-dimensional
Metric

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lian, Guanqin ; Zhou, Shuming ; Hsieh, Sun-Yuan ; Liu, Jiafei ; Chen, Gaolin ; Wang, Yihong. / Performance evaluation on hybrid fault diagnosability of regular networks. In: Theoretical Computer Science. 2019 ; Vol. 796. pp. 147-153.
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Performance evaluation on hybrid fault diagnosability of regular networks. / Lian, Guanqin; Zhou, Shuming; Hsieh, Sun-Yuan; Liu, Jiafei; Chen, Gaolin; Wang, Yihong.

In: Theoretical Computer Science, Vol. 796, 03.12.2019, p. 147-153.

Research output: Contribution to journalArticle

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