Distributed Fault Detection for Wireless Sensor Based on Weighted Average

Ji, Sai; Yuan, Shenfang; Ma, Tinghuai; Tan, Chang

doi:10.1109/nswctc.2010.21

Cited by 38 publications

(30 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the distance as a weight, the influence of correlation degree of various neighbors is taken into account. On the other hand, the authors in [5] and [6] assign weights to neighbors according to their confidence levels. Given this condition, the potential statuses (good or faulty) of different neighbors are taken into consideration.…”

Section: Related Workmentioning

confidence: 99%

Temporal and spatial correlation based distributed fault detection in wireless sensor networks

Akhtar

Wang

et al. 2015

2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE)

View full text Add to dashboard Cite

Since wireless sensor networks are usually used for long-term monitoring in harsh environments, sensor nodes are vulnerable to faults. Function fault can lead to immediate node breakdown, while data fault makes the node generate erroneous sensor data. Faulty data results in incorrect estimation of the environment and causes unnecessary consumption of the network resources. Therefore, it is necessary to detect faulty data in real time. In this paper, a new distributed fault detection algorithm is proposed, which is based on the temporal and spatial correlation of the sensor data. With the proposed algorithm, faulty data is detected and discarded locally, so that the network resource consumption is minimized and the processing burden of the terminal is reduced. Simulation results show that the proposed algorithm improves detection accuracy, as compared to the baseline distributed fault detection algorithms.

show abstract

Section: Related Workmentioning

confidence: 99%

Temporal and spatial correlation based distributed fault detection in wireless sensor networks

Akhtar

Wang

et al. 2015

2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE)

View full text Add to dashboard Cite

show abstract

“…Statistical techniques are usually adopted to identify the sensors that are suspected to be faulty [8,9,10,11]. Besides the sensing data of neighbors, the sensor’s own historical data are also used.…”

Section: Introductionmentioning

confidence: 99%

Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids

Shao

Guo

Qiu

2017

Sensors

View full text Add to dashboard Cite

Due to the increasingly important role in monitoring and data collection that sensors play, accurate and timely fault detection is a key issue for wireless sensor networks (WSNs) in smart grids. This paper presents a novel distributed fault detection mechanism for WSNs based on credibility and cooperation. Firstly, a reasonable credibility model of a sensor is established to identify any suspicious status of the sensor according to its own temporal data correlation. Based on the credibility model, the suspicious sensor is then chosen to launch fault diagnosis requests. Secondly, the sending time of fault diagnosis request is discussed to avoid the transmission overhead brought about by unnecessary diagnosis requests and improve the efficiency of fault detection based on neighbor cooperation. The diagnosis reply of a neighbor sensor is analyzed according to its own status. Finally, to further improve the accuracy of fault detection, the diagnosis results of neighbors are divided into several classifications to judge the fault status of the sensors which launch the fault diagnosis requests. Simulation results show that this novel mechanism can achieve high fault detection ratio with a small number of fault diagnoses and low data congestion probability.

show abstract

“…Panda et al [16] proposed a distributed self fault diagnosis algorithm to detect faults using three sigma edit test. Ji et al [26] proposed a distributed fault detection method for WSN using weighted average by comparing own data with the mean of neighbors data. Clouquerer et al [27] proposed a fault tolerance method for the sensor network to detect the target collaboratively.…”

Section: Introductionmentioning

confidence: 99%

Self soft fault detection based routing protocol for vehicular ad hoc network in city environment

Bhoi

Khilar

2015

Wireless Netw

View full text Add to dashboard Cite

Routing protocols in vehicular ad hoc network (VANET) mainly depends on the correct information provided by the neighbor vehicles in the form of beacons. If the on board unit is soft faulty, it provides incorrect data and reduces the performance of the system. In this paper, a novel self soft fault detection based routing protocol is proposed for VANET in city environment to send the data quickly to the destination by detecting the soft faulty vehicles. The vehicle itself detects whether it is soft faulty or fault free by using the decisions made by the neighbor vehicles and exclude itself from the routing process. The data is forwarded through the fault free vehicles in a mostly connected path. The best path is selected at every junction by finding path values for the paths connected to the junction. The path with the minimum path value is selected as the next path through which the data is forwarded. The performance of the fault detection method is evaluated by fault detection rate and false alarm rate. Simulation results show that, proposed protocol performs better than GyTAR, A-STAR, P-GEDIR, and GSR routing protocols in terms of end-to-end delay, number of network gaps, and path length.

show abstract

Distributed Fault Detection for Wireless Sensor Based on Weighted Average

Cited by 38 publications

References 10 publications

Temporal and spatial correlation based distributed fault detection in wireless sensor networks

Temporal and spatial correlation based distributed fault detection in wireless sensor networks

Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids

Self soft fault detection based routing protocol for vehicular ad hoc network in city environment

Contact Info

Product

Resources

About