A New Measure for Locally t-Diagnosable Under PMC Model

Meirun Chen, D. Frank Hsu, Cheng Kuan Lin*

*此作品的通信作者

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

PMC model is the test-based diagnosis which a vertex performs the diagnosis by testing the neighbor vertices via the edges between them. Hsu and Tan proposed two structures to diagnose a vertex. But these structures don’t always exist for any vertex. Here, we propose a new testing structure to diagnose a vertex under PMC model to solve the problem above. It can fit more general networks. Let S be a set of faulty edges of the n-dimensional hypercube Qn. Using this structure, we show that every vertex u of Qn is degQn-S(u) -diagnosable if δ(Qn- S) ≥ 2, degQn-S(x)+degQn-S(y)≥5 for every two adjacent vertices x and y in Qn- S, and n≥ 5.

原文English
主出版物標題Computing and Combinatorics - 27th International Conference, COCOON 2021, Proceedings
編輯Chi-Yeh Chen, Wing-Kai Hon, Ling-Ju Hung, Chia-Wei Lee
發行者Springer Science and Business Media Deutschland GmbH
頁面306-316
頁數11
ISBN(列印)9783030895426
DOIs
出版狀態Published - 2021
事件27th International Conference on Computing and Combinatorics, COCOON 2021 - Tainan, Taiwan
持續時間: 24 10月 202126 10月 2021

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13025 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference27th International Conference on Computing and Combinatorics, COCOON 2021
國家/地區Taiwan
城市Tainan
期間24/10/2126/10/21

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