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
收藏
页码：258 / 264
页数：7
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