• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1131-1135
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• 2014

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.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.615-620
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• 2005

Sensor networks are usually composed of tens or thousands of tiny devices with limited resources. Because of their limited resources, there will often be some faulty nodes within the network. As nodes in some certain regions rely on each other to route the information gathered by different sensors to a base station (sink), the network should be able to detect a non-operational node in order to determine new paths for routing the information. Failure detection, which identifies the faulty nodes, is rather necessary in sensor networks and a very important research issue. The detection of a non-operational node can be performed using Consensus Algorithm with the purpose of achieving agreement about a node which is supposed to be faulty (non-operational). In this work, we discuss the application of a Consensus Algorithm to sensor node called 'mote'. Our experimental results show that it works efficiently for identifying faulty nodes in sensor networks.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.20-28
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• 2014

This paper proposes a faulty node detection scheme that performs collective monitoring of a distributed networked control systems using interval weighting factor. The algorithm is designed to observe every node's behavior collectively based on the pseudo-random Bose-Chaudhuri-Hocquenghem (BCH) code. Each node sends a single BCH bit simultaneously as a replacement for the cyclic redundancy check (CRC) code. The fault judgement is performed by performing sequential check of observed detected error to guarantee detection accuracy. This scheme can be used for detecting and preventing serious damage caused by node failure. Simulation results show that the fault judgement based on decision pattern gives comprehensive summary of suspected faulty node.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.386-390
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• 2007

센서 네트워크 시스템은 한정된 자원을 갖는 센서노드들을 광대한 영역에 설치하여 새로운 정보를 수집 하고 모니터링 하는 기능을 한다. 센서 노드와 센서의 고장(Sensor node faulty or Sensor faulty)은 열악한 설치 환경이나 제한된 리소스에 의해 종종 발생 되는데 이들 고장은 네트워크 내에서 요구되는 양질의 서비스 제공에 많은 문제를 가져온다. 본 논문에서는 센서 노드의 고장 검출 알고리즘으로 알려져 있는 Consensus 알고리즘과 센서노드에서 사용되는 센서의 고장을 검출할 수 있는 localized faulty sensor detection 알고리즘을 혼합하여 시스템에 안정된 서비스를 제공할 수 있는 방법을 제안하며 실제 시뮬레이션과 제작된 실험장치에 적용함으로써 그 유용성을 확인하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.760-765
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• 2007

The sensor network system which has limited resources is deployed in a wide area and plays an important role of gethering information and monitoring. Generally, fault of sensor nodes which was caused by limited resources and poor environment happens. Futhermore, this fault poses many problems related with required quality of whole network. In this paper, new fault detection algorithm which utilizes both consensus algorithm and localized faulty sensor detection scheme is proposed. To verify the feasibility of the proposed scheme, some simulation and experiment are carried out.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3965-3982
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• 2015

Event detection is one of the key issues in many wireless sensor network (WSN) applications. The uncertainties that are derived from the instability of sensor node, measurement noise and incomplete sampling would influence the performance of event detection to a large degree. Many of the present researches described the sensor readings with crisp values, which cannot adequately handle the uncertainties inhered in the imprecise sensor readings. In this paper, a fault-tolerant event detection algorithm is proposed based on Dempster-Shafer (D-S) theory (also called evidence theory). Instead of crisp values, all possible states of the event are represented by the Basic Probability Assignment (BPA) functions, with which the output of each sensor node are characterized as weighted evidences. The combination rule was subsequently applied on each sensor node to fuse the evidences gathered from the neighboring nodes to make the final decision on whether the event occurs. Simulation results show that even 20% nodes are faulty, the accuracy of the proposed algorithm is around 80% for event region detection. Moreover, 97% of the error readings have been corrected, and an improved detection capability at the boundary of the event region is gained by 75%. The proposed algorithm can enhance the detection accuracy of the event region even in high error-rate environment, which reflects good reliability and robustness. The proposed algorithm is also applicable to boundary detection as it performs well at the boundary of the event.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.385-388
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• 2006

비선형 주성분 분석은 기존에 널리 알려져 있는 주성분 분석기법과 유사한 다변수 데이터 분석을 위한 새로운 접근 방법이다. 비선형 주성분 분석은 AANN(Auto Associative Neural Network)으로 PCA와 마찬가지로 변수들 간에 존재하는 상관관계를 제거함으로써 고차의 다변수 데이터를 정보의 손실을 최소화하면서 최소 차원의 데이터로 변환하는 기법이다. AANN 기반 센서노드 고장검출 기법을 실제 센서 네트워크에 적용하여 봄으로써 센서 드리프트 등과 같은 센서 고장의 검출 및 유효한 센서 보정 성능을 확인하였다.