Predictability of Fault Events for Decentralized Stochastic Discrete-Event Systems Based on Dynamic Observations and Polynomial-Time Verification

Fault prediction of discrete-event systems (DESs) is to predict the fault prior to its occurrence such that effective measures can be taken. We investigate the issue of the fault copredictability of stochastic DESs (SDESs) in a decentralized setting under dynamic observations. It is supposed that the observation of events of the system is not fixed in advance. To perform the decentralized prediction of SEDSs, a D-coverifier from the given stochastic system with multiple local projections is constructed and a necessary and sufficient condition for the verification of D-copredictability by the D-coverifier is presented, which is polynomial-time complexity.

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Published
2024-11-29
DOI
https://doi.org/10.1109/irac63143.2024.10871349
Primary Topic
Software Reliability and Analysis Research
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article
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article

Predictability of Fault Events for Decentralized Stochastic Discrete-Event Systems Based on Dynamic Observations and Polynomial-Time Verification

Yilin Wu, Fuchun Liu, Ruqi Zhou, Hui Liao
Software Reliability and Analysis Research
article

Predictability of Fault Events for Decentralized Stochastic Discrete-Event Systems Based on Dynamic Observations and Polynomial-Time Verification

Yilin Wu, Fuchun Liu, Ruqi Zhou, Hui Liao
article en

Abstract

Fault prediction of discrete-event systems (DESs) is to predict the fault prior to its occurrence such that effective measures can be taken. We investigate the issue of the fault copredictability of stochastic DESs (SDESs) in a decentralized setting under dynamic observations. It is supposed that the observation of events of the system is not fixed in advance. To perform the decentralized prediction of SEDSs, a D-coverifier from the given stochastic system with multiple local projections is constructed and a necessary and sufficient condition for the verification of D-copredictability by the D-coverifier is presented, which is polynomial-time complexity.

Guangdong University Of Finances and Economics (CN), Guangdong University of Education (CN)
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Software Reliability and Analysis Research
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