The 2-good-neighbour diagnosability of modified bubble-sort graphs under the PMC and MM* model

被引：2

作者：

Wang, Yanling ^{[1
]}

Wang, Shiying ^{[1
]}

机构：

[1] Henan Normal Univ, Henan Engn Lab Big Data Stat Anal & Optimal Contr, Sch Math & Informat Sci, Xinxiang, Henan, Peoples R China

来源：

SYSTEMS SCIENCE & CONTROL ENGINEERING | 2020年 / 8卷 / 01期

基金：

美国国家科学基金会;

关键词：

Interconnection network; diagnosability; modified bubble-sort graph; 2-good-neighbour; CAYLEY-GRAPHS; CONDITIONAL DIAGNOSABILITY; CONNECTIVITY;

D O I：

10.1080/21642583.2020.1746211

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The study of interconnection networks is a hot topic for multiprocessor systems. Diagnosability plays an important role in the study of interconnection networks. A new measure for fault diagnosis of a system is proposed by Peng et al. in 2012. It is called g-good-neighbour diagnosability which restrains every fault-free vertex containing at least g fault-free neighbours. The n-dimensional modified bubble-sort graph is a special Cayley graph. In this paper, we give that the 2-good-neighbour diagnosability of under the PMC model is 4n-5 for and the 2-good-neighbour diagnosability of under the model is 4n-5 for .

引用

页码：258 / 264

页数：7

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