• 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 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.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.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04c
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• pp.54-57
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• 2008

A new modular Lateral Information Propagation Networks can be implemented in a IC chip with the circuit VLSI technology for detection of bad materials. The proposed modular architecture is propagated the neural network through inter module connections. For such inter module connections, the host(computer or logic) mediates the exchange of information among modules. Also border nodes in each module have capacitors for temporarily retaining the information from outer modules. For detecting of Faulty Insulator, $4\;{\times}\;4$ neural network modules has been designed and simulation of interpolation with the designed networks has been done.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.126-131
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• 2008

Wireless Sensor Network(WSNs) consists of small sensor nodes with sensing, computation, and wireless communication capabilities. It has new information collection scheme and monitoring solution for a variety of applications. Faults occurring to sensor nodes are common due to the limited resources and the harsh environment where the sensor nodes are deployed. In order to ensure the network quality of service it is necessary for the WSN to be able to detect the faulty sensors and take necessary actions for the reconstruction of the lost sensor data caused by fault as earlier as possible. In this paper, we propose an recursive PCA-based fault detection and lost data reconstruction algorithm for sensor networks. Also, the performance of proposed scheme was verified with simulation studies.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.203-208
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• 2016

This paper presents a fault detection and data processing algorithm for acoustic sensor systems using the multiple sensor algorithm that has originally developed for the wireless sensor nodes. The multiple sensor algorithm can increase the reliability of the sensor systems by utilizing and comparing the measurements of the multiple sensors. In the acoustic sensor system, the equivalent sound level($L_{eq}$) is used to detect the faulty sensor. The experiment was conducted to demonstrate the feasibility of the multiple acoustic sensor algorithm, and the results show that the algorithm can detect the faulty sensor and validate the data.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2123-2135
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• 1997

In this paepr, we consider resistive shorts on drain-source, drain-gate, and gate-source as well as opens in MOSFETs included in typical memory cell of VLSI SRAM. Behavior of memeory is observed by analyzing voltage at storage nodes of memeory and IDDQ(quiescent power supply current) through PSPICE simulation. Using this behavioral analysis, an effective testing algorithm of complexity O(N) which can be applied to both functional testing and IDDQ testing simultaeously is proposed. Built-In Self Test(BIST) circuit which detects faults in memories and Built-In Current Sensor(BICS) which monitors the power supply bus for abnormalities in quescent current are developed and imprlemented to improve the quality and efficiency of testing. Implemented BIST and BICS circuits can detect locations of faults and defects in order to repair faulty memories.