scholarly journals Cooperative fault-detection mechanism with high accuracy and bounded delay for underwater sensor networks

2009 ◽  
Vol 9 (2) ◽  
pp. 143-153 ◽  
Author(s):  
Pu Wang ◽  
Jun Zheng ◽  
Cheng Li
Keyword(s):  
Sensor Networks ◽  
Fault Detection ◽  
High Accuracy ◽  
Underwater Sensor Networks ◽  
Detection Mechanism ◽  
Bounded Delay

scholarly journals An Uncertainty-Based Distributed Fault Detection Mechanism for Wireless Sensor Networks

Sensors ◽  
2014 ◽  
Vol 14 (5) ◽  
pp. 7655-7683 ◽  
Author(s):  
Yang Yang ◽  
Zhipeng Gao ◽  
Hang Zhou ◽  
Xuesong Qiu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Wireless Sensor ◽  
Detection Mechanism ◽  
Distributed Fault Detection

Cost-Effective Lock-Stepped EDDI: Transient Fault Detection Mechanism

2012 ◽  
Vol 35 (12) ◽  
pp. 2562
Author(s):  
Chao WANG ◽  
Zhong-Chuan FU ◽  
Hong-Song CHEN ◽  
Gang CUI
Keyword(s):  
Fault Detection ◽  
Cost Effective ◽  
Detection Mechanism ◽  
Transient Fault

Multi-AUV Aided Cooperative 3D-localization for Underwater Sensor Networks

2020 ◽  
Vol 13 (1) ◽  
pp. 80-90 ◽  
Author(s):  
Meiyan Zhang ◽  
Wenyu Cai
Keyword(s):  
Sensor Networks ◽  
Mean Squared Error ◽  
Autonomous Underwater Vehicles ◽  
Estimation Method ◽  
Location Estimation ◽  
Underwater Sensor Networks ◽  
Coverage Ratio ◽  
Minimum Mean Squared Error ◽  
3D Localization ◽  
Localization Scheme

Background: Effective 3D-localization in mobile underwater sensor networks is still an active research topic. Due to the sparse characteristic of underwater sensor networks, AUVs (Autonomous Underwater Vehicles) with precise positioning abilities will benefit cooperative localization. It has important significance to study accurate localization methods. Methods: In this paper, a cooperative and distributed 3D-localization algorithm for sparse underwater sensor networks is proposed. The proposed algorithm combines with the advantages of both recursive location estimation of reference nodes and the outstanding self-positioning ability of mobile AUV. Moreover, our design utilizes MMSE (Minimum Mean Squared Error) based recursive location estimation method in 2D horizontal plane projected from 3D region and then revises positions of un-localized sensor nodes through multiple measurements of Time of Arrival (ToA) with mobile AUVs. Results: Simulation results verify that the proposed cooperative 3D-localization scheme can improve performance in terms of localization coverage ratio, average localization error and localization confidence level. Conclusion: The research can improve localization accuracy and coverage ratio for whole underwater sensor networks.

Security based on Received Signal Strength in Localization for Underwater Sensor Networks

2016 ◽  
Vol 1 (2) ◽  
pp. 1-7
Author(s):  
Karamjeet Kaur ◽  
Gianetan Singh Sekhon
Keyword(s):  
Sensor Networks ◽  
Threshold Value ◽  
Critical Issue ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Research Subjects ◽  
Malicious Nodes ◽  
Intermediate Node ◽  
End To End Delay ◽  
End To End

Underwater sensor networks are envisioned to enable a broad category of underwater applications such as pollution tracking, offshore exploration, and oil spilling. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security critical issue as underwater sensor networks are typically deployed in harsh environments. Localization is one of the latest research subjects in UWSNs since many useful applying UWSNs, e.g., event detecting. Now day’s large number of localization methods arrived for UWSNs. However, few of them take place stability or security criteria. In purposed work taking up localization in underwater such that various wireless sensor nodes get localize to each other. RSS based localization technique used remove malicious nodes from the communication intermediate node list based on RSS threshold value. Purposed algorithm improves more throughput and less end to end delay without degrading energy dissipation at each node. The simulation is conducted in MATLAB and it suggests optimal result as comparison of end to end delay with and without malicious node.

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