The g-good-neighbor diagnosability of product networks under the PMC model

IF 1 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Zhao Wang , Yaping Mao , Sun-Yuan Hsieh , Ralf Klasing
{"title":"The g-good-neighbor diagnosability of product networks under the PMC model","authors":"Zhao Wang ,&nbsp;Yaping Mao ,&nbsp;Sun-Yuan Hsieh ,&nbsp;Ralf Klasing","doi":"10.1016/j.ic.2025.105341","DOIUrl":null,"url":null,"abstract":"<div><div>The concept of neighbor connectivity originated from the assessment of the subversion of espionage networks caused by underground resistance movements, and it has now been applied to measure the disruption of networks caused by cascading failures through neighbors. In this paper, we give two necessary and sufficient conditions of the existence of <em>g</em>-good-neighbor diagnosability. We introduce a new concept called <em>g</em>-good neighbor cut-component number (gc number for short), which has close relation with <em>g</em>-good-neighbor diagnosability. Sharp lower and upper bounds of the gc number of general graphs in terms of the <em>g</em>-good neighbor connectivity have been proposed, which provide a formula to compute the <em>g</em>-good-neighbor diagnosability for general graphs (therefore for Cartesian product graphs). As their applications, we get the exact values or bounds for the gc numbers and <em>g</em>-good-neighbor diagnosability of grid, torus networks and generalized cubes.</div></div>","PeriodicalId":54985,"journal":{"name":"Information and Computation","volume":"307 ","pages":"Article 105341"},"PeriodicalIF":1.0000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information and Computation","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S089054012500077X","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

The concept of neighbor connectivity originated from the assessment of the subversion of espionage networks caused by underground resistance movements, and it has now been applied to measure the disruption of networks caused by cascading failures through neighbors. In this paper, we give two necessary and sufficient conditions of the existence of g-good-neighbor diagnosability. We introduce a new concept called g-good neighbor cut-component number (gc number for short), which has close relation with g-good-neighbor diagnosability. Sharp lower and upper bounds of the gc number of general graphs in terms of the g-good neighbor connectivity have been proposed, which provide a formula to compute the g-good-neighbor diagnosability for general graphs (therefore for Cartesian product graphs). As their applications, we get the exact values or bounds for the gc numbers and g-good-neighbor diagnosability of grid, torus networks and generalized cubes.
PMC模型下产品网络的g近邻可诊断性
邻居连通性的概念起源于对地下抵抗运动引起的间谍网络颠覆的评估,现在已被应用于测量通过邻居的级联故障引起的网络中断。本文给出了g-近邻可诊断性存在的两个充分必要条件。引入了与g-好邻居可诊断性密切相关的g-好邻居截断分量数(gc数)的概念。提出了一般图的g-好邻居连通性的gc数的明显下界和上界,从而提供了计算一般图(即笛卡尔积图)的g-好邻居可诊断性的公式。作为它们的应用,我们得到了网格、环面网络和广义立方体的gc数和g近邻可诊断性的精确值或界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信