Technology Research on the Fault Diagnosis of Wireless Sensor Network System

2013 ◽  
Vol 846-847 ◽  
pp. 442-445
Author(s):  
Chun Lin He
Keyword(s):  
Fault Diagnosis ◽  
Sensor Network ◽  
Simulation Experiment ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network System ◽  
Technology Research ◽  
Spatio Temporal ◽  
Network Fault

The fault diagnosis technology have emerged and developed rapidly with the development of wireless sensor networks and requirements of applications improve. This paper describes two commonly used sensor network fault modeling. What is more, in order to solve this problem that sensor nodes are vulnerable and therefore produce wrong data, the paper proposes a distributed fault detecting algorithm based on spatio-temporal correlation among data of adjacent nodes. The simulation experiment shows that the algorithm can efficiently detect errors in the network and very few errors are introduced.

scholarly journals Fault-Tolerant Anomaly Detection Method in Wireless Sensor Networks

Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 236 ◽  
Author(s):  
Nengsong Peng ◽  
Weiwei Zhang ◽  
Hongfei Ling ◽  
Yuzhao Zhang ◽  
Lixin Zheng
Keyword(s):  
Sensor Networks ◽  
Anomaly Detection ◽  
Sensor Network ◽  
Detection Method ◽  
Fault Tolerant ◽  
False Negative ◽  
False Negative Rate ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Wireless Sensor

A key issue in wireless sensor network applications is how to accurately detect anomalies in an unstable environment and determine whether an event has occurred. This instability includes the harsh environment, node energy insufficiency, hardware and software breakdown, etc. In this paper, a fault-tolerant anomaly detection method (FTAD) is proposed based on the spatial-temporal correlation of sensor networks. This method divides the sensor network into a fault neighborhood, event and fault mixed neighborhood, event boundary neighborhood and other regions for anomaly detection, respectively, to achieve fault tolerance. The results of experiment show that under the condition that 45% of sensor nodes are failing, the hit rate of event detection remains at about 97% and the false negative rate of events is above 92%.

Dynamic Function Alternation to Realize Robust Wireless Sensor Network

2012 ◽  
Vol 3 (3) ◽  
pp. 17-34 ◽  
Author(s):  
Toshiaki Miyazaki
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Distributed Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network System ◽  
Dynamic Function ◽  
Disaster Monitoring

In this paper, a distributed algorithm to realize a dynamic function alternation is proposed. The algorithm enables sensor nodes to take over the damaged functions of their neighboring sensor nodes automatically in a wireless sensor network. After describing the concept of the function alternation, the algorithm is explained in detail with some evaluation results. Comparing the results obtained using the proposed algorithm with those obtained using non-function alternation methods shows that the proposed algorithm makes the initial functionality of each sensor function sustainable even if some sensor nodes are damaged. A wireless sensor network system dedicated to disaster monitoring is also introduced, as an application of the proposed function alternation algorithm.

Wireless Sensor Network Fault Diagnosis Method of Optimization Research and Simulation

2013 ◽  
Vol 347-350 ◽  
pp. 955-959
Author(s):  
Qiang Li
Keyword(s):  
Wireless Sensor Network ◽  
Fault Diagnosis ◽  
Sensor Network ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Wireless Sensor ◽  
Sensor Fault ◽  
Diagnosis Method ◽  
Network Fault

The traditional method of wireless sensor network fault diagnosis based on linear modeling rather than actually complicated and nod-linear relationship results in error data and leads to wrong decisions, therefore, this paper presents a sensor fault diagnosis method based on ARIMA and LSSVM integration control system which used to diagnosis sensor fault whose results are input LSSVM to fusion and get the final results of fault diagnosis. The simulation test results show that the proposed method improves the sensor node fault diagnosis accuracy, reduce the false negative rate and false positive rate.

Design of Wireless Sensor Network System Based on Computer Control Technology

2014 ◽  
Vol 608-609 ◽  
pp. 517-520
Author(s):  
Qing Hua Xu ◽  
Chang Wan Liu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Software Design ◽  
Computer Control ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network System ◽  
Zigbee Technology ◽  
Function Module ◽  
Monitoring Software

In this paper we design a wireless sensor network of Zigbee technology, which consists of sensor nodes, sink nodes and monitoring software design. Through laboratory test, the design of the system is stable and reliable. Although the system can meet the requirements of Zigbee wireless communication hardware, but part of system hardware is relatively simple. If it is applied to the more complex place, we must add the corresponding module in the hardware and software. Adding node function module and the monitoring function in the Zigbee wireless network, it will meet the actual needs.

Kuiper test and autoregressive model-based approach for wireless sensor network fault diagnosis

2014 ◽  
Vol 21 (3) ◽  
pp. 829-839 ◽  
Author(s):  
Xiaohang Jin ◽  
Tommy W. S. Chow ◽  
Yi Sun ◽  
Jihong Shan ◽  
Bill C. P. Lau
Keyword(s):  
Wireless Sensor Network ◽  
Fault Diagnosis ◽  
Sensor Network ◽  
Autoregressive Model ◽  
Wireless Sensor ◽  
Model Based ◽  
Kuiper Test ◽  
Network Fault

Outlier Detection and Decision Tree for Wireless Sensor Network Fault Diagnosis

2021 ◽  
Author(s):  
Irfanur Ilham Febriansyah ◽  
Whika Cahyo Saputro ◽  
Galih Ridha Achmadi ◽  
Fadila Arisha ◽  
Dara Tursina ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Sensor Network ◽  
Outlier Detection ◽  
Wireless Sensor ◽  
Network Fault

scholarly journals Analysis of Epidemic Model for Performance Evaluation of Rechargeable Wireless Sensor Network

2021 ◽  
Author(s):  
Shashank Awasthi ◽  
◽  
Naresh Kumar ◽  
Pramod Kumar Srivastava ◽  
Rudra Pratap Ojha ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network System ◽  
Security Threat ◽  
Malware Propagation ◽  
Charging Mechanism ◽  
Coverage And Connectivity

Wireless sensor network (WSN) is a decentralized network system which consists of sensor nodes, and these nodes are connected through wireless link. Due to decentralized network system and resource constraint WSN faces security threat. Malware (malicious signals, worm, Trajan horse, virus etc.) attacks on the sensor node of WSN and make them paralyze and steal information from the network. Malware attack also increases the energy consumption of Sensor nodes of WSN. It just begins to spread from an infected node, and spread across the entire WSN with the help of neighboring nodes. Therefore, security of WSN against attack of malware is an inescapable need. On the basis of earlier works and consideration of charging mechanism of sensor nodes, and considering the effect of coverage and connectivity, proposed a SILRD (Susceptible - Infectious – Low Energy – Recovered –Dead) model with vital dynamics. The propose model investigates the dynamics of malware propagation in WSN and also explain sensor node’s energy consumption. The system’s stability has analyzed in terms of local and global of malware-free and endemic equilibrium. For the investigation of system dynamics, the expression of basic reproduction number has computed, which is also utilized to analyze state of malware in WSN. The effect of charging, coverage and connectivity is explained in this paper.

A Novel and Smart Wireless Sensor Network System for Real Time Aquaculture Applications

2020 ◽  
Author(s):  
Lakshmi Narayana Thalluri ◽  
Jitendra Prasad Ayodhya ◽  
Yuva Raju Chava ◽  
Bhimeswara Anjaneya Prasad Tati
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network System

An Effective Congestion Control Algorithm based on Traffic Assignment and Reassignment in Wireless Sensor Network

2020 ◽  
Vol 13 (8) ◽  
pp. 1166-1174
Author(s):  
Chao Wang
Keyword(s):  
Wireless Sensor Network ◽  
Congestion Control ◽  
Sensor Network ◽  
Traffic Assignment ◽  
Transmission Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Detection ◽  
Detection Technology ◽  
Average Transmission

Background: It is important to improve the quality of service by using congestion detection technology to find the potential congestion as early as possible in wireless sensor network. Methods: So an improved congestion control scheme based on traffic assignment and reassignment algorithm is proposed for congestion avoidance, detection and mitigation. The congestion area of the network is detected by predicting and setting threshold. When the congestion occurs, sensor nodes can be recovery quickly from congestion by adopting reasonable method of traffic reassignment. And the method can ensure the data in the congestion areas can be transferred to noncongestion areas as soon as possible. Results: The simulation results indicate that the proposed scheme can reduce the number of loss packets, improve the throughput, stabilize the average transmission rate of source node and reduce the end-to-end delay. Conclusion: : So the proposed scheme can enhance the overall performance of the network. Keywords: wireless sensor network; congestion control; congestion detection; congestion mitigation; traffic assignment; traffic reassignment.

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