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...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/23247/ |
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| Summary: | 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. |
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