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http://dx.doi.org/10.5302/J.ICROS.2014.14.8019

Markov Model-Driven in Real-time Faulty Node Detection for Naval Distributed Control Networked Systems  

Noh, Dong-Hee (Dept. of IT Convergence, Kumoh National Institute of Technology)
Kim, Dong-Seong (Dept. of Electronic Engineering, Kumoh National Institute of Technology)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.20, no.11, 2014 , pp. 1131-1135 More about this Journal
Abstract
This paper proposes the enhanced faulty node detection scheme with hybrid algorithm using Markov-chain model on BCH (Bose-Chaudhuri-Hocquenghem) code in naval distributed control networked systems. The probabilistic model-driven approach, on Markov-chain model, in this paper uses the faulty weighting interval factors, which are based on the BCH code. In this scheme, the master node examines each slave-nodes continuously using three defined states : Good, Warning, Bad-state. These states change using the probabilistic calculation method. This method can improve the performance of detecting the faulty state node more efficiently. Simulation results show that the proposed method can improve the accuracy in faulty node detection scheme for real-time naval distributed control networked systems.
Keywords
faulty node detection; naval distributed control networked systems; weighting factors; BCH; Markov-Chain model;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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