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A novel dual-attribute fault diagnosis measure for hypercube networks.

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Title: A novel dual-attribute fault diagnosis measure for hypercube networks.
Authors: Zhuo, Nengjin1 (AUTHOR) 15038792269@163.com, Zhang, Shumin1,2,3 (AUTHOR) zhangshumin@qhnu.edu.cn, Chang, Jou-Ming4 (AUTHOR) spade@ntub.edu.tw, Ma, Haoyu5 (AUTHOR) mahaoyu_22@bupt.edu.cn
Source: Discrete Applied Mathematics. Sep2026, Vol. 390, p40-56. 17p.
Subjects: Fault diagnosis, Hypercube networks (Computer networks), Multiprocessors, Fault tolerance (Engineering)
Abstract: Fault diagnosis technology is a key technique for maintaining the stable operation of multi-processor systems. By designing and applying diagnostic models and algorithms, multi-processor systems can execute specific instructions and utilize diagnostic algorithms to analyze the result, thereby accurately identifying faulty processors in the system. Different types of fault sets cause varying degrees of damage to a system. Therefore, many scholars have conducted in-depth research on those fault sets that may cause significant damage to a system and proposed various diagnosability metrics to evaluate the diagnostic capability of a system, such as component diagnosability and H -structure diagnosability. This paper introduces a novel diagnosability measure c t r g (G) to evaluate the diagnostic capability of a system G regarding g -extra r -component fault sets. Through an in-depth analysis of the hypercube network topology, we determine that c t 3 1 (Q n) = 6 n − 15 under the PMC model and c t 3 1 (Q n) = 5 n − 11 under the MM* model. [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
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Header DbId: egs
DbLabel: Engineering Source
An: 193680371
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A novel dual-attribute fault diagnosis measure for hypercube networks.
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  Data: <searchLink fieldCode="AR" term="%22Zhuo%2C+Nengjin%22">Zhuo, Nengjin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 15038792269@163.com</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Shumin%22">Zhang, Shumin</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> zhangshumin@qhnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Chang%2C+Jou-Ming%22">Chang, Jou-Ming</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> spade@ntub.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Ma%2C+Haoyu%22">Ma, Haoyu</searchLink><relatesTo>5</relatesTo> (AUTHOR)<i> mahaoyu_22@bupt.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Discrete+Applied+Mathematics%22">Discrete Applied Mathematics</searchLink>. Sep2026, Vol. 390, p40-56. 17p.
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  Data: <searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Hypercube+networks+%28Computer+networks%29%22">Hypercube networks (Computer networks)</searchLink><br /><searchLink fieldCode="DE" term="%22Multiprocessors%22">Multiprocessors</searchLink><br /><searchLink fieldCode="DE" term="%22Fault+tolerance+%28Engineering%29%22">Fault tolerance (Engineering)</searchLink>
– Name: Abstract
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  Data: Fault diagnosis technology is a key technique for maintaining the stable operation of multi-processor systems. By designing and applying diagnostic models and algorithms, multi-processor systems can execute specific instructions and utilize diagnostic algorithms to analyze the result, thereby accurately identifying faulty processors in the system. Different types of fault sets cause varying degrees of damage to a system. Therefore, many scholars have conducted in-depth research on those fault sets that may cause significant damage to a system and proposed various diagnosability metrics to evaluate the diagnostic capability of a system, such as component diagnosability and H -structure diagnosability. This paper introduces a novel diagnosability measure c t r g (G) to evaluate the diagnostic capability of a system G regarding g -extra r -component fault sets. Through an in-depth analysis of the hypercube network topology, we determine that c t 3 1 (Q n) = 6 n − 15 under the PMC model and c t 3 1 (Q n) = 5 n − 11 under the MM* model. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  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=193680371
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.dam.2026.04.005
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 40
    Subjects:
      – SubjectFull: Fault diagnosis
        Type: general
      – SubjectFull: Hypercube networks (Computer networks)
        Type: general
      – SubjectFull: Multiprocessors
        Type: general
      – SubjectFull: Fault tolerance (Engineering)
        Type: general
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      – TitleFull: A novel dual-attribute fault diagnosis measure for hypercube networks.
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            NameFull: Zhang, Shumin
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            NameFull: Chang, Jou-Ming
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            NameFull: Ma, Haoyu
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          Dates:
            – D: 15
              M: 09
              Text: Sep2026
              Type: published
              Y: 2026
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              Value: 390
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            – TitleFull: Discrete Applied Mathematics
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