Distributed fault source detection and topology accommodation design of wireless sensor networks

Zhao, Ye; He, Xiao; Zhou, Donghua

doi:10.1109/iecon.2017.8216957

Cited by 4 publications

(3 citation statements)

References 18 publications

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“…Apart from fault diagnosis in the background of distributed systems, some literature also focuses on time-varying system topologies. Based on a distributed fault detection filter, [51] handled faults by removing faulty nodes from the system to prevent propagation of sensing errors. Stability analysis of switching topology of Markov jump systems was proposed in [52], where a novel Lyapunov function as well as a sufficient condition of stability was given.…”

Section: Addressing the Challenges Induced By Distributed Architecturementioning

confidence: 99%

Model‐based fault diagnosis of networked systems: A survey

Song

2021

Asian Journal of Control

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This paper reviews the latest development of fault diagnosis techniques of networked systems. Considering various challenges raised by unreliable local sensors, signal digitization, data transmission, as well as distributed architecture, recent progress on model‐based fault diagnosis of networked systems are overviewed. We summarize the typical application examples and the typical treatment methods related to scientific problems for better understanding the framework of this area. Some promising future fault diagnosis techniques in various scenarios, such as distributed systems, with communication protocols, with cyber security issues, with intelligent algorithm challenges, as well as within active fault diagnosis framework are discussed.

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Section: Addressing the Challenges Induced By Distributed Architecturementioning

confidence: 99%

Model‐based fault diagnosis of networked systems: A survey

Song

2021

Asian Journal of Control

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“…(ii) Rule-based methods derive heuristic rules and constraints for the sensor readings often by exploiting domain or expert knowledge. Such approaches can range from adaptive thresholds of the sensor data [33] over signature-based fault detection [34] up to applying distributed state filters on the sensor data [35].…”

Section: Sensor Data Analysismentioning

confidence: 99%

An Open-Source Wireless Sensor Node Platform with Active Node-Level Reliability for Monitoring Applications

Widhalm

Goeschka

Kästner

2021

Sensors

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In wireless sensor networks, the quality of the provided data is influenced by the properties of the sensor nodes. Often deployed in large numbers, they usually consist of low-cost components where failures are the norm, even more so in harsh outdoor environments. Current fault detection techniques, however, consider the sensor data alone and neglect vital information from the nodes’ hard- and software. As a consequence, they can not distinguish between rare data anomalies caused by proper events in the sensed data on one side and fault-induced data distortion on the other side. In this paper, we contribute with a novel, open-source sensor node platform for monitoring applications such as environmental monitoring. For long battery life, it comprises mainly low-power components. In contrast to other sensor nodes, our platform provides self-diagnostic measures to enable active node-level reliability. The entire sensor node platform including the hardware and software components has been implemented and is publicly available and free to use for everyone. Based on an extensive and long-running practical experiment setup, we show that the detectability of node faults is improved and the distinction between rare but proper events and fault-induced data distortion is indeed possible. We also show that these measures have a negligible overhead on the node’s energy efficiency and hardware costs. This improves the overall reliability of wireless sensor networks with both, long battery life and high-quality data.

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“…Failure within the cluster is identified by the cluster head by comparing the sensed data of that member node and its neighbor nodes while detection process for cluster head's failure is implemented by the detector. Ye Zhao et al [12] integrated a distributed model for fault detection and topology accommodation. The proposed approach is based on distributed state filtering.…”

Section: Introductionmentioning

confidence: 99%

Energy Attentive Pre-fault Detection Mechanism with Multilevel Transmission for Distributed Wireless Sensor Network

Talmale¹,

Mundukur²,

Thakare³

2019

RIA

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To recognize the vision of ambient intelligence, wireless sensor networks (WSNs) are broadly used to invent real time and smart applications. Energy has been a major concern in sensor networks. Another challenging issue of wireless sensor network is to discover the imperfect node and recover them to maintain network topology. Enhancement of network lifetime, reliability and scalability also depends on fault detection and recovery mechanism. Distributed Energy Attentive Pre Fault Detection Mechanism is proposed in this work for pre fault detection and multipath routing. The novel idea behind this approach is to recognize the sensor fault in advanced and performed the improvement action based on notification parameter like acknowledgement not received, residual energy is below threshold value and hope count distance. It enables a predesor node to rapidly identify and efficiently categories the next energy aware shortest path, upon steering failure, rather than relying from the starting place. Extensive simulations are performed and result demonstrates that the proposed algorithms perform well on various performance indicator metrics such as throughput, energy consumption, packet drop ratio, and communication delay.

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Distributed fault source detection and topology accommodation design of wireless sensor networks

Cited by 4 publications

References 18 publications

Model‐based fault diagnosis of networked systems: A survey

Model‐based fault diagnosis of networked systems: A survey

An Open-Source Wireless Sensor Node Platform with Active Node-Level Reliability for Monitoring Applications

Energy Attentive Pre-fault Detection Mechanism with Multilevel Transmission for Distributed Wireless Sensor Network

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