Performance evaluation on hybrid fault diagnosability of regular networks

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

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)147-153
頁數7
期刊Theoretical Computer Science
796
DOIs
出版狀態Published - 2019 十二月 3

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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