Weighted-Median Based Distributed Fault Detection for Wireless Sensor Networks

Gao, Jianliang; Xu, Yongjun; Li, Xiaowei

doi:10.1360/jos181208

Cited by 47 publications

(25 citation statements)

References 13 publications

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“…The data reduction is to keep the classification ability of data under the same conditions, delete the redundant, irrelevant or unimportant data, to make the data classification becomes simple and clear [8]. This article uses the improvement proposed above reduction of attribute reduction of decision table data of variable precision rough set based on that, after a record of decision table reduction processing on behalf of a class has the same regularity properties of samples, so that the decision rule has higher adaptability.…”

Section: Fault Diagnosis In Wireless Sensor Network Node Based On Romentioning

confidence: 99%

Novel Approach of Fault Diagnosis in Wireless Sensor Networks Node Based On Rough Set and Neural Network Model

Xu¹,

Zhang²,

Lin³

et al. 2016

IJFGCN

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Section: Fault Diagnosis In Wireless Sensor Network Node Based On Romentioning

confidence: 99%

Novel Approach of Fault Diagnosis in Wireless Sensor Networks Node Based On Rough Set and Neural Network Model

Xu¹,

Zhang²,

Lin³

et al. 2016

IJFGCN

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“…Because of faulty sensors in WSN, network quality of service will get degrade and create the huge burden on the limited energy of the sensor node. A weighted median fault detection scheme (WMFDS) is proposed [10] in which the author uses the spatial correlation of sensor measurements for the detection of faulty nodes in the network and it was evaluated for both binary decisions and real number measurements by weighting the neighbor's measurement. For eliminating unpredictable local decisions while performing distributed decision fusion author [11] proposed the Collaborative sensor fault detection (CSFD) scheme.…”

Section: Related Workmentioning

confidence: 99%

A fault tolerant approach to extend network life time of wireless sensor network

Kshirsagar¹,

Jirapure²

2015

2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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In a wireless sensor network the delivery of the data packet from source to destination may be failed for various reasons and major due to failure-prone environment of networks. This may happen due to the topology changes, node failure due to battery, exhaust or breakdown of the communication module in the wireless node and results in the link failure. This paper addressed the major problem of link failure due to the failure of the nodes in the WSN and with the aim of providing robust solutions to satisfy the QoS-based stern end-to-end requirements of communication networks. In this paper, we propose the new solution by modifying the existing extended fully distributed cluster-based routing algorithm (EFDCB). In this proposed algorithm the faulty nodes or nodes that are more prone to failure in the every cluster of the network get identified by exchanging data and mutually testing among neighbor nodes. When we established the path between source and destination these faulty nodes get excluded in the path selection process and more stable, less prone to failure path will be formed. The performance of this new modified fault-tolerant fully distributed cluster-based routing algorithm is evaluated by simulating it in NS2 environment. Simulation results show that it performs better than the existing algorithm and provide novel solution for fault detection and fault management along the QoS paths and achieves a high degree of fault tolerance.

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“…In [5] authors applied correlation to the sensors measurements to detect nodes failures. They introduced a method to give weights to neighbors and then measure the difference of reading.…”

Section: Rerelated Workmentioning

confidence: 99%

Analytical Modeling for reliability in cluster based Wireless Sensor Networks

Ahmed

2014

2014 9th International Conference on Computer Engineering &Amp; Systems (ICCES)

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In most Wireless Sensor Networks applications users would expect to achieve good service in terms of reliable retrieved accurate data. One technique to improve the level of data accuracy is to use fault tolerance techniques such as redundancy that would cause the energy of the system to deplete quickly. In this paper we address the problem of reliable wireless sensor network and provide the desi g n and the analysis of an algorithm that model cluster-based structured Wireless SensorNetworks with the objective of achieving suitable reliability level requirements to extend the whole system lifetime. Reliability is defined as the probability that a sensor node will perform its intended function during a specified period of time under stated conditions. We analyze the effect of redundancy on the system reliability and the energy consumption level of the Wireless Sensor Networks model. Throughout the analysis we derived an expression for both the reliability and the energy consumption in terms of redundancy level parameter. Parameterizin g the reliability and energy consumption would give the system designer the ability to select the suitable value of the redundancy level in order to satisfy different performance criteria such as maximizing the system reliability and achieving minimum energy consumption at the same time.

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Weighted-Median Based Distributed Fault Detection for Wireless Sensor Networks

Abstract: Gao JL, Xu YJ, Li XW. Weighted-Median based distributed fault detection for wireless sensor networks.

Cited by 47 publications

References 13 publications

Novel Approach of Fault Diagnosis in Wireless Sensor Networks Node Based On Rough Set and Neural Network Model

Novel Approach of Fault Diagnosis in Wireless Sensor Networks Node Based On Rough Set and Neural Network Model

A fault tolerant approach to extend network life time of wireless sensor network

Analytical Modeling for reliability in cluster based Wireless Sensor Networks

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