Energy-aware test connection assignment for the self-diagnosis of a wireless sensor network

Weber, Andréa; Kutzke, Alexander Robert; Chessa, Stefano

doi:10.1007/s13173-012-0057-7

Cited by 9 publications

(5 citation statements)

References 21 publications

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“…Weber et al [8] propose a strategy of mutual tests among the sensor nodes in a region where t numbers of faulty sensor nodes are present such that the system graph representing the region of the WSNs is t-diagnosable. Weber et al presented a diagnosis approach namely energyefficient test assignment without reciprocal tests [7] which are based on their previous work [8].Chen et al [9] propose and evaluate a localized fault detection algorithm named Distributed Fault Detection to identify the faulty sensors. Mahapatro and Khilar [10] propose an On-line distributed fault diagnosis method called cluster-based distributed fault diagnosis algorithm.…”

Section: Related Workmentioning

confidence: 99%

An Improved Distributed Fault Diagnosis Algorithm in Wireless Sensor Networks

Lin¹,

Huang

Zhang

2017

Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

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Abstract-In wireless sensor networks (WSNs), nodes fault diagnosis is the important measure for the continuous monitoring service. Efficient and accurate methods for diagnose nodes fault is a hot research topic in the field of WSNs in the recent years. This paper propose an improved distributed fault diagnosis method namely Cross-Space Distributed Fault Diagnosis (CS-DFD) which follows the DFD algorithm, building high-dimensional vector space model through the collected information from each node, establishing the cross type of sliding window through its historical data and the data from neighbor nodes, setting the cross direction customizable weights of fault. Ultimately, achieving the goal of fault diagnosis by detecting abnormal vector and threshold. The experimental results show that it has reduced the amount of calculation; simplified harsh conditions of fault judgments; reduced the consumption of electricity, etc. which in DFD algorithm. Comparing with the traditional DFD algorithm, the fault diagnosis accuracy improved by 5.14%, the fault of false alarm ratio (FAR) decreased by 2.01% and the time of diagnosis has shortened obviously.

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Section: Related Workmentioning

confidence: 99%

An Improved Distributed Fault Diagnosis Algorithm in Wireless Sensor Networks

Lin¹,

Huang

Zhang

2017

Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

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“…Users can inquire and investigate relevant data through the task manager node, and they can also send operating orders through it to achieve remote control and monitoring. There is a large application prospect of WSN, such as the national defense and military, monitoring industrial process, monitoring production of agriculture and forestry, monitoring of environment, urban traffic control and management, rescue of disaster, remote control of dangerous areas [9,10].…”

Section: Structure Of Monitoring Device and Its Principlementioning

confidence: 99%

The Development of the Remote Wireless Monitoring Device for Toxic Gases

Zhu

Tang

et al. 2013

AMR

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For the scene where there is a toxic gas leak, in order to detect the gas quickly and safely and make the effective solutions, the project of monitoring toxic gases in a remote wireless way and the process of the development is proposed in this paper. The device developed in this paper includes several wireless sensor network (WSN) nodes and one hand-held terminal, and the sensor module of WSN node is composed of several chemical gas sensors. The nodes will be sent to the scene by ground robots or unmanned aerial vehicles and make up the WSN monitoring system automatically, to achieve an aim of monitoring the toxic gas in real time. The experiment results show that the device can deal with the emergencies about the leak of toxic gas efficiently. And it has the advantages of low power consumption, high cost performance, self-forming network, anti-interference. Its suitable to monitor the toxic gas in various environments of industrial production and chemical scene of accident and unexpected occasions where there is a leak of toxic gas.

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“…Most of the fault detection schemes [19,[23][24][25] are designed to detect permanent faults. In [2], a class of countand-threshold mechanisms collectively named α-count is suggested, which are able to discriminate between transient faults and intermittent faults in computing systems.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Approach to Discriminate the Persistence of Faults in Wireless Sensor Networks

Mahapatro

Khilar

2012

ISRN Sensor Networks

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This paper presents a parametric fault detection algorithm which can discriminate the persistence (permanent, intermittent, and transient) of faults in wireless sensor networks. The main characteristics of these faults are the amount the fault appears. We adopt this state-holding time to discriminate transient from intermittent faults. Neighbor-coordination-based approach is adopted, where faulty sensor nodes are detected based on comparisons between neighboring nodes and dissemination of the decision made at each node. Simulation results demonstrate the robustness of the work at varying transient fault rate.

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Energy-aware test connection assignment for the self-diagnosis of a wireless sensor network

Cited by 9 publications

References 21 publications

An Improved Distributed Fault Diagnosis Algorithm in Wireless Sensor Networks

An Improved Distributed Fault Diagnosis Algorithm in Wireless Sensor Networks

The Development of the Remote Wireless Monitoring Device for Toxic Gases

An Adaptive Approach to Discriminate the Persistence of Faults in Wireless Sensor Networks

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