Neighbor connectivity of hypercube-based compound network.
Saved in:
| Title: | Neighbor connectivity of hypercube-based compound network. |
|---|---|
| Authors: | Li, Yifan1 (AUTHOR) llyfliyifan@163.com, Zhou, Shuming1,2,3 (AUTHOR) zhoushuming@fjnu.edu.cn, Zhang, Qifan1 (AUTHOR) zqf_1995@163.com |
| Source: | Discrete Applied Mathematics. May2026, Vol. 384, p1-15. 15p. |
| Subjects: | Hypercube networks (Computer networks), Graph connectivity, Computer networks, Computer network reliability |
| Abstract: | For a network G , the subversion at the vertex set (resp., edge set) of G is defined as the removal of the closed neighborhood of the vertex set (resp., all end vertices of the edge set) from G , where the vertex set (resp., edge set) is referred as subverted vertices (resp., edges). Neighbor connectivity and edge neighbor connectivity serve as key indicators for assessing the subversion of spy networks and network disruptions throughout the deletion of closed neighborhood. The neighbor connectivity κ N B (G) (resp., edge neighbor connectivity λ N B (G)) of a network G is defined as the minimum number of subverted vertices (resp., edges) required to disconnect it, make it empty or complete (resp., trivial). Gu et al. (IEEE Trans. Netw. Sci. Eng. 11 (5) (2024) 1-13) conjectured that whether κ NB (G) = δ (G) − 1 2 + 1 holds for all compound graphs G constructed by the underlying block Q n. In this paper, we solve this conjecture and determine the (edge) neighbor connectivity of a class of hypercube-based compound network, including half hypercube, hierarchical hypercube, hierarchical cubic network and dual-cube-like network. In addition, we present network vulnerability analysis algorithms based on neighborhood fault pattern. To evaluate their effectiveness, taking the half hypercube, hierarchical cubic network and real-world network dwt-918 as examples, we perform experimental simulations to analyze both the cardinality distribution of subverted vertices and topological configurations of survival graph. [ABSTRACT FROM AUTHOR] |
| Copyright of Discrete Applied Mathematics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 192002131 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Neighbor connectivity of hypercube-based compound network. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Yifan%22">Li, Yifan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> llyfliyifan@163.com</i><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Shuming%22">Zhou, Shuming</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> zhoushuming@fjnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Qifan%22">Zhang, Qifan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zqf_1995@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Discrete+Applied+Mathematics%22">Discrete Applied Mathematics</searchLink>. May2026, Vol. 384, p1-15. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Hypercube+networks+%28Computer+networks%29%22">Hypercube networks (Computer networks)</searchLink><br /><searchLink fieldCode="DE" term="%22Graph+connectivity%22">Graph connectivity</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+networks%22">Computer networks</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+reliability%22">Computer network reliability</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: For a network G , the subversion at the vertex set (resp., edge set) of G is defined as the removal of the closed neighborhood of the vertex set (resp., all end vertices of the edge set) from G , where the vertex set (resp., edge set) is referred as subverted vertices (resp., edges). Neighbor connectivity and edge neighbor connectivity serve as key indicators for assessing the subversion of spy networks and network disruptions throughout the deletion of closed neighborhood. The neighbor connectivity κ N B (G) (resp., edge neighbor connectivity λ N B (G)) of a network G is defined as the minimum number of subverted vertices (resp., edges) required to disconnect it, make it empty or complete (resp., trivial). Gu et al. (IEEE Trans. Netw. Sci. Eng. 11 (5) (2024) 1-13) conjectured that whether κ NB (G) = δ (G) − 1 2 + 1 holds for all compound graphs G constructed by the underlying block Q n. In this paper, we solve this conjecture and determine the (edge) neighbor connectivity of a class of hypercube-based compound network, including half hypercube, hierarchical hypercube, hierarchical cubic network and dual-cube-like network. In addition, we present network vulnerability analysis algorithms based on neighborhood fault pattern. To evaluate their effectiveness, taking the half hypercube, hierarchical cubic network and real-world network dwt-918 as examples, we perform experimental simulations to analyze both the cardinality distribution of subverted vertices and topological configurations of survival graph. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Discrete Applied Mathematics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=192002131 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.dam.2025.12.049 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1 Subjects: – SubjectFull: Hypercube networks (Computer networks) Type: general – SubjectFull: Graph connectivity Type: general – SubjectFull: Computer networks Type: general – SubjectFull: Computer network reliability Type: general Titles: – TitleFull: Neighbor connectivity of hypercube-based compound network. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Yifan – PersonEntity: Name: NameFull: Zhou, Shuming – PersonEntity: Name: NameFull: Zhang, Qifan IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 0166218X Numbering: – Type: volume Value: 384 Titles: – TitleFull: Discrete Applied Mathematics Type: main |
| ResultId | 1 |