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

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Arunanshu Mahapatro ◽  
Pabitra Mohan Khilar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Detection Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Transient Fault ◽  
Intermittent Faults ◽  
Parametric Fault ◽  
Simulation Results

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.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

scholarly journals Distributed Beacon Drifting Detection for Localization in Unstable Environments

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ming Xia ◽  
Peiliang Sun ◽  
Xiaoyan Wang ◽  
Yan Jin ◽  
Qingzhang Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Location Information ◽  
Detection Accuracy ◽  
Research Issue ◽  
Fundamental Research

Localization is a fundamental research issue in wireless sensor networks (WSNs). In most existing localization schemes, several beacons are used to determine the locations of sensor nodes. These localization mechanisms are frequently based on an assumption that the locations of beacons are known. Nevertheless, for many WSN systems deployed in unstable environments, beacons may be moved unexpectedly; that is, beacons are drifting, and their location information will no longer be reliable. As a result, the accuracy of localization will be greatly affected. In this paper, we propose a distributed beacon drifting detection algorithm to locate those accidentally moved beacons. In the proposed algorithm, we designed both beacon self-scoring and beacon-to-beacon negotiation mechanisms to improve detection accuracy while keeping the algorithm lightweight. Experimental results show that the algorithm achieves its designed goals.

scholarly journals Online fault diagnosis of wireless sensor networks

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Arunanshu Mahapatro ◽  
Pabitra Khilar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Diagnosis ◽  
Wireless Sensor ◽  
Transient Faults ◽  
Intermittent Faults ◽  
Detection Latency ◽  
Time Redundancy ◽  
Simulation Results ◽  
Time And Energy

AbstractThis paper proposes an adaptive online distributed solution for fault diagnosis in wireless sensor networks (WSNs). Fault diagnosis is achieved by comparing the heartbeat message generated by neighboring nodes and dissemination of decision made at each node. Time redundancy is used to detect the intermittent faults since an intermittent fault will not occur consistently. The diagnosis performance degradation due to intermittent faults in sensing and transient faults in communication is analyzed. A near optimal trade-off between detection latency and number of tests required to detect intermittent faults is obtained. Simulation results are provided and they show that this work performs better, from both time and energy complexity viewpoint.

scholarly journals Research on Pseudo-Node Detection Algorithm in Wireless Sensor Networks

2017 ◽  
Vol 13 (03) ◽  
pp. 113
Author(s):  
Wenjin Yu ◽  
Yong Li ◽  
Yuangeng Xu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Detection Algorithm ◽  
Comprehensive Analysis ◽  
Attack Detection ◽  
Wireless Sensor ◽  
Font Size ◽  
Simulation Results ◽  
Sensor Security

<span style="font-family: 'Times New Roman',serif; font-size: 12pt; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;">With the wide application of the wireless sensor network, the security of the sensor network is becoming increasingly important. In this paper, based on node ranging, a new intrusion node detection algorithm has been proposed for external pseudo-node detection in wireless sensor networks. The presence of the nodes under copying-attack and the pseudo-nodes in the network can be detected through inter-node ranging with appropriate use of various sensors of nodes themselves and comprehensive analysis of ranging results. Operating in a stand-alone or embedded manner, this method has remedied the defects in the traditional principle of attack detection. The simulation results show that the proposed method has excellent applicability in wireless sensor security detection.</span>

An Improved Sensor Positioning for Wireless Sensor Networks

2014 ◽  
Vol 716-717 ◽  
pp. 1322-1325
Author(s):  
Jin Tao Lin ◽  
Guang Yu Fan ◽  
Wen Hong Liu ◽  
Ying Da Hu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Positioning Accuracy ◽  
Positioning Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Sensor Positioning

Sensor positioning is a fundamental block in various location-dependent applications of wireless sensor networks. In order to improve the positioning accuracy without increasing the complex and cost of sensor nodes, an improve sensor positioning method is proposed for wireless sensor networks. In the method, after receiving the broadcasting message of the neighboring anchor nodes, the sensor nodes calculate a modifying factor of the change of the signal strength. And they modify the distances between themselves and neighboring anchor nodes with the modifying factor. Simulation results show that the proposed method can obtain a high positioning accuracy.

Localization in Wireless Sensor Networks in Beacon Drifting Scenarios

2012 ◽  
Vol 562-564 ◽  
pp. 1234-1239
Author(s):  
Ming Xia ◽  
Qing Zhang Chen ◽  
Yan Jin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Probability Density ◽  
Sensor Nodes ◽  
Density Model ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Scenarios Simulation ◽  
Simulation Results

The beacon drifting problem occurs when the beacon nodes move accidentally after deployment. In this occasion, the localization results of sensor nodes in the network will be greatly affected and become inaccurate. In this paper, we present a localization algorithm in wireless sensor networks in beacon drifting scenarios. The algorithm first uses a probability density model to calculate the location reliability of each node, and in localization it will dynamically choose nodes with highest location reliabilities as beacon nodes to improve localization accuracy in beacon drifting scenarios. Simulation results show that the proposed algorithm achieves its design goals.

scholarly journals A Multi-Target Tracking and Detection Algorithm for Wireless Sensor Networks

2021 ◽  
Vol 15 ◽  
pp. 661-665
Author(s):  
Gang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Detection Algorithm ◽  
Wireless Sensor ◽  
Main Function ◽  
Multiple Target ◽  
Target State ◽  
Multi Target Tracking ◽  
Simulation Results

There are a large number of sensor nodes in wireless sensor network, whose main function is to process data scientifically, so that it can better sense and cooperate. In the network coverage, it can comprehensively collect the main information of the monitoring object, and send the monitoring data through short-range wireless communication to the gateway. Although there are many applications in WSNs, a multi-Target tracking and detection algorithm and the optimization problem of the wireless sensor networks are discussed in this paper. It can be obviously seen from the simulation results that this node cooperative program using particle CBMeMBer filtering algorithm can perfectly handle multi-target tracking, even if the sensor model is seriously nonlinear. Simulation results show that the tracking - forecasting data association scheme applying GM-CBMeMBer, which is proposed in this paper, runs well in identifying multiple target state, and can improve the estimation accuracy of multiple target state.

An Efficient Fitness Function for Clustering of Wireless Sensor Networks

2020 ◽  
Vol 10 (3) ◽  
pp. 318-324
Author(s):  
Atiieh Hoseinpour ◽  
Mojtaba Jafari Lahijani ◽  
Mohammad Hosseinpour ◽  
Javad Kazemitabar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fitness Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Evolutionary Clustering ◽  
Fitness Functions ◽  
Field Sensor ◽  
Simulation Results ◽  
And Control

Background & Objective: A sensor network is composed of a large number of sensor nodes that are deployed to perform measurement and/or command and control in a field. Sensor nodes are battery powered devices and replacement or recharging of their batteries may not be feasible. One of the major challenges with sensory wireless networks is excessive energy consumption in nodes. Clustering is one of the methods that has been offered for resolving this issue. In this paper, we pursue evolutionary clustering and propose a new fitness function that har-nesses multiple propagation indices. Methods: In this paper we develop an efficient fitness function by first selecting the best clusters, and then selecting the best attribution of cluster to clusters. The distance between the nodes and relevant cluster heads was used for the mathematical modelling necessary. In the end we develop the fitness function equation by using normalization of the raw data. Results: Simulation results show improvement compared to previous fitness functions in clustering of the wireless sensor networks.

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