Characterization of cyclic local diagnosability of interconnection networks.
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| Title: | Characterization of cyclic local diagnosability of interconnection networks. |
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| Authors: | Zheng, Weixing1 (AUTHOR), Zhou, Shuming2 (AUTHOR), Cheng, Eddie3 (AUTHOR), Yang, Lulu1 (AUTHOR) |
| Source: | Computer Journal. Jun2026, Vol. 69 Issue 6, p1039-1049. 11p. |
| Subjects: | Fault diagnosis, Multiprocessors, Computer network architectures |
| Abstract: | With the growing scale and complexity of high-performance computing systems, ensuring reliability through robust fault diagnosis becomes increasingly critical. System-level diagnosis plays a key role in identifying faulty processors and maintaining system stability of multiprocessor systems. However, traditional diagnosability, as a global reliability metric for multiprocessor systems, overlooks local diagnostic capability, topological criticality, and fault distribution. In order to better capture the local characteristics of a system around a given node, this work proposes a novel fault diagnosis strategy, called cyclic local diagnosability, where the cyclic fault pattern requires that at least two components contain cycles. We propose some characterizations of cyclic local diagnosability of interconnection networks under PMC and MM* models. As applications, we determine the cyclic local diagnosabilities of data center network DCell (|$D_{k,n}$|), |$(n,k)$| -star graph (|$S_{n,k}$|) and |$(n,k)$| -bubble-sort graph (|$B_{n,k}$|) under PMC and MM* models. Finally, we show the superiority of the cyclic local diagnosability through comparison with other conditional diagnosabilities. [ABSTRACT FROM AUTHOR] |
| Copyright of Computer Journal is the property of Oxford University Press / USA 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 194728444 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Characterization of cyclic local diagnosability of interconnection networks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zheng%2C+Weixing%22">Zheng, Weixing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhou%2C+Shuming%22">Zhou, Shuming</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cheng%2C+Eddie%22">Cheng, Eddie</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Lulu%22">Yang, Lulu</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computer+Journal%22">Computer Journal</searchLink>. Jun2026, Vol. 69 Issue 6, p1039-1049. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Multiprocessors%22">Multiprocessors</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+architectures%22">Computer network architectures</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: With the growing scale and complexity of high-performance computing systems, ensuring reliability through robust fault diagnosis becomes increasingly critical. System-level diagnosis plays a key role in identifying faulty processors and maintaining system stability of multiprocessor systems. However, traditional diagnosability, as a global reliability metric for multiprocessor systems, overlooks local diagnostic capability, topological criticality, and fault distribution. In order to better capture the local characteristics of a system around a given node, this work proposes a novel fault diagnosis strategy, called cyclic local diagnosability, where the cyclic fault pattern requires that at least two components contain cycles. We propose some characterizations of cyclic local diagnosability of interconnection networks under PMC and MM* models. As applications, we determine the cyclic local diagnosabilities of data center network DCell (|$D_{k,n}$|), |$(n,k)$| -star graph (|$S_{n,k}$|) and |$(n,k)$| -bubble-sort graph (|$B_{n,k}$|) under PMC and MM* models. Finally, we show the superiority of the cyclic local diagnosability through comparison with other conditional diagnosabilities. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computer Journal is the property of Oxford University Press / USA 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/comjnl/bxag009 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1039 Subjects: – SubjectFull: Fault diagnosis Type: general – SubjectFull: Multiprocessors Type: general – SubjectFull: Computer network architectures Type: general Titles: – TitleFull: Characterization of cyclic local diagnosability of interconnection networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zheng, Weixing – PersonEntity: Name: NameFull: Zhou, Shuming – PersonEntity: Name: NameFull: Cheng, Eddie – PersonEntity: Name: NameFull: Yang, Lulu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 00104620 Numbering: – Type: volume Value: 69 – Type: issue Value: 6 Titles: – TitleFull: Computer Journal Type: main |
| ResultId | 1 |
