Distributed Topology Control Protocols for Underwater Sensor Networks

2016 ◽  
Author(s):  
Hina Nasir ◽  
Nadeem Javaid ◽  
Shaharyar Mahmood ◽  
Umar Qasim ◽  
Zahoor Ali Khan ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Topology Control ◽  
Underwater Sensor Networks ◽  
Control Protocols

scholarly journals Topology Control for Energy-Efficient Localization in Mobile Underwater Sensor Networks Using Stackelberg Game

2019 ◽  
Vol 68 (2) ◽  
pp. 1487-1500 ◽  
Author(s):  
Yali Yuan ◽  
Chencheng Liang ◽  
Megumi Kaneko ◽  
Xu Chen ◽  
Dieter Hogrefe
Keyword(s):  
Sensor Networks ◽  
Energy Efficient ◽  
Topology Control ◽  
Stackelberg Game ◽  
Underwater Sensor Networks

scholarly journals A Cluster Sleep-Wake Scheduling Algorithm Based on 3D Topology Control in Underwater Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 156 ◽  
Author(s):  
Wenbo Zhang ◽  
Jing Wang ◽  
Guangjie Han ◽  
Xinyue Zhang ◽  
Yongxin Feng
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Topology Control ◽  
Scheduling Algorithm ◽  
Basic Unit ◽  
Underwater Sensor Networks ◽  
Efficient Operation ◽  
Underwater Sensor Network ◽  
Temporary Control ◽  
3D Topology

3D topology control in underwater sensor networks is of great significance to ensuring reliable and efficient operation of the network. In this paper, by analyzing the characteristics of an underwater sensor network, we take the cube as the basic unit to perform 3D partition of the monitoring area, define the 3D partition unit and basic cluster structure of the underwater sensor network, and arrange rotating temporary control nodes in the cluster. Then, a cluster sleep-wake scheduling algorithm is proposed that compares the remaining node energy. It selects the node with the largest remaining energy as the working node, and the remaining nodes complete the transition of dormancy and waiting states as long as they reach the preset dormancy time. The node state settings of this phase are completed by the temporary control node. Temporary control nodes selecting and sleep-wake scheduling are used in the algorithm through 3D topology control, which reduces energy consumption and guarantees maximum sensing coverage of the entire network and the connection rate of active nodes. Simulation results further verify the effectiveness of the proposed algorithm.

scholarly journals The Effects of Using Some Different Types of Learning Automata on Presentation of Adaptive Neighbor-Based and Energy Efficient Topology Control Protocols in Wireless Sensor Networks

2017 ◽  
Vol 2 (2) ◽  
pp. 6-17
Author(s):  
Shekufeh Shafeie ◽  
M. R. Meybodi
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Topology Control ◽  
Control Point ◽  
Learning Automata ◽  
Point Of View ◽  
Q Model ◽  
Control Protocols ◽  
Model Environment

The high number of nodes and dynamic and periodic topological changes, as well as constraints in the physical size of nodes, energy resources, and power of processing are some characteristics of sensor networks that make them different from other networks. One method to overcome these constraints is topology control with the aim of reducing energy consumption and increasing the network’s capacity, which has the most influence on the network’s efficiency, especially in terms of energy consumption and lifetime. In  consideration of learning  Automata’s abilities, such as low computational load and adaptability to changes via low environmental feedbacks, in this paper, neighbor-based topology control protocols based on learning Automata have been proposed somehow that all nodes are equipped with Automata. The nodes try to adapt their selected actions with required conditions for creating a connected and energy efficient network by selecting the best radio range for themselves. This approach finally forms a proper topology, and in this way it lowers the network’s energy consumption in its lifetime. The exclusive characteristic of these methods is the high number of transmission ranges that each node can select as transmission radius. In the first proposed protocol, a P-model environment is used for learning phase, but in the second proposed protocol, a Q-model environment is applied. Simulation results show favorite functionality of proposed protocols in comparison with some other similar protocols from topology control point of view, as well as high improvement of achieved results for the Q-model environment.

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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