### 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 t_{h} ^{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 |

卷 | 796 |

DOIs | |

出版狀態 | Published - 2019 十二月 3 |

### 指紋

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### 引用此文

*Theoretical Computer Science*,

*796*, 147-153. https://doi.org/10.1016/j.tcs.2019.09.004

}

*Theoretical Computer Science*, 卷 796, 頁 147-153. https://doi.org/10.1016/j.tcs.2019.09.004

**Performance evaluation on hybrid fault diagnosability of regular networks.** / Lian, Guanqin; Zhou, Shuming; Hsieh, Sun-Yuan; Liu, Jiafei; Chen, Gaolin; Wang, Yihong.

研究成果: Article

TY - JOUR

T1 - Performance evaluation on hybrid fault diagnosability of regular networks

AU - Lian, Guanqin

AU - Zhou, Shuming

AU - Hsieh, Sun-Yuan

AU - Liu, Jiafei

AU - Chen, Gaolin

AU - Wang, Yihong

PY - 2019/12/3

Y1 - 2019/12/3

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85071963515&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071963515&partnerID=8YFLogxK

U2 - 10.1016/j.tcs.2019.09.004

DO - 10.1016/j.tcs.2019.09.004

M3 - Article

AN - SCOPUS:85071963515

VL - 796

SP - 147

EP - 153

JO - Theoretical Computer Science

JF - Theoretical Computer Science

SN - 0304-3975

ER -