An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems.
In this paper, predictive hybrid redundancy has been extended to large-scale control systems comprising n modules. In m-out-of-n systems, if m-out-of-n modules are in agreement, the system can report consensus; otherwise the system fails. While in our new extension, if there is no agreement, a histo...
| Main Authors: | , , , |
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| Format: | Article |
| Published: |
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/23247/ |
| _version_ | 1848844703867338752 |
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| author | Syed Mohamed, Syed Abdul Rahman Al-Haddad Jantan, Adznan Karimi, Abbas Zarafshan, Faraneh |
| author_facet | Syed Mohamed, Syed Abdul Rahman Al-Haddad Jantan, Adznan Karimi, Abbas Zarafshan, Faraneh |
| author_sort | Syed Mohamed, Syed Abdul Rahman Al-Haddad |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In this paper, predictive hybrid redundancy has been extended to large-scale control systems comprising n modules. In m-out-of-n systems, if m-out-of-n modules are in agreement, the system can report consensus; otherwise the system fails. While in our new extension, if there is no agreement, a history record of previous successful result(s) is used to predict the output. In order to analyze the reliability of this system, we present a Markov model based on which the reliability has been computed and compared with m-out-of-n redundancy. The results of simulation demonstrated that the new redundancy improves overall system reliability in all examined scenarios, especially when the number m is large. |
| first_indexed | 2025-11-15T08:35:09Z |
| format | Article |
| id | upm-23247 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T08:35:09Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-232472014-11-04T05:24:18Z http://psasir.upm.edu.my/id/eprint/23247/ An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. Syed Mohamed, Syed Abdul Rahman Al-Haddad Jantan, Adznan Karimi, Abbas Zarafshan, Faraneh In this paper, predictive hybrid redundancy has been extended to large-scale control systems comprising n modules. In m-out-of-n systems, if m-out-of-n modules are in agreement, the system can report consensus; otherwise the system fails. While in our new extension, if there is no agreement, a history record of previous successful result(s) is used to predict the output. In order to analyze the reliability of this system, we present a Markov model based on which the reliability has been computed and compared with m-out-of-n redundancy. The results of simulation demonstrated that the new redundancy improves overall system reliability in all examined scenarios, especially when the number m is large. 2011 Article PeerReviewed Syed Mohamed, Syed Abdul Rahman Al-Haddad and Jantan, Adznan and Karimi, Abbas and Zarafshan, Faraneh (2011) An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. International Journal of the Physical Sciences, 6 (30). 6981 - 6994. ISSN 1992-1950 10.5897/IJPS11.912 |
| spellingShingle | Syed Mohamed, Syed Abdul Rahman Al-Haddad Jantan, Adznan Karimi, Abbas Zarafshan, Faraneh An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. |
| title | An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. |
| title_full | An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. |
| title_fullStr | An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. |
| title_full_unstemmed | An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. |
| title_short | An efficient Markov model for reliability analysis of predictive hybrid m-out-of-n systems. |
| title_sort | efficient markov model for reliability analysis of predictive hybrid m-out-of-n systems. |
| url | http://psasir.upm.edu.my/id/eprint/23247/ http://psasir.upm.edu.my/id/eprint/23247/ |