Research on reliability of complex network for estimating network reliability.
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| Title: | Research on reliability of complex network for estimating network reliability. |
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| Authors: | Xue Gang Chen1 gxcjsj@163.com |
| Source: | Journal of Intelligent & Fuzzy Systems. 2017, Vol. 32 Issue 5, p3551-3560. 10p. |
| Subjects: | Computer network reliability, Computer reliability, Reliability of telecommunication, Algorithms, Monte Carlo method |
| Abstract: | Network reliability is an important index in measuring the reliability of large-sized network, but network reliability calculation is a NP-hard problem, and simulation is a feasible approach to estimating network reliability. Aiming at the problem of reliability evaluation in a complex network, develop a general scheme that combines Crude Monte Carlo and event-driven, and a novel reliability assessment method based on event-driven is put forward. The unbiased and the accurate estimation of the proposed method are analyzed from a theoretical point of view. Experimental results demonstrate that the proposed method is more efficient than other algorithms, such as high simulation efficiency, fine estimation accuracy and greatly reducing the algorithm complexity. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. 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 | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 123568207 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Research on reliability of complex network for estimating network reliability. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xue+Gang+Chen%22">Xue Gang Chen</searchLink><relatesTo>1</relatesTo><i> gxcjsj@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Intelligent+%26+Fuzzy+Systems%22">Journal of Intelligent & Fuzzy Systems</searchLink>. 2017, Vol. 32 Issue 5, p3551-3560. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+network+reliability%22">Computer network reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+reliability%22">Computer reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Reliability+of+telecommunication%22">Reliability of telecommunication</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Network reliability is an important index in measuring the reliability of large-sized network, but network reliability calculation is a NP-hard problem, and simulation is a feasible approach to estimating network reliability. Aiming at the problem of reliability evaluation in a complex network, develop a general scheme that combines Crude Monte Carlo and event-driven, and a novel reliability assessment method based on event-driven is put forward. The unbiased and the accurate estimation of the proposed method are analyzed from a theoretical point of view. Experimental results demonstrate that the proposed method is more efficient than other algorithms, such as high simulation efficiency, fine estimation accuracy and greatly reducing the algorithm complexity. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. 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=123568207 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3233/JIFS-169291 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 3551 Subjects: – SubjectFull: Computer network reliability Type: general – SubjectFull: Computer reliability Type: general – SubjectFull: Reliability of telecommunication Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Monte Carlo method Type: general Titles: – TitleFull: Research on reliability of complex network for estimating network reliability. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xue Gang Chen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: 2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 10641246 Numbering: – Type: volume Value: 32 – Type: issue Value: 5 Titles: – TitleFull: Journal of Intelligent & Fuzzy Systems Type: main |
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