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Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks.

Jun Liu^1,2, Peng Jiang³, Feng Wu⁴

¹College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China. liujun@163.com.

Sensors (Basel, Switzerland)

|December 29, 2016

Summary

This summary is machine-generated.

Node drift in underwater sensor networks (UWSNs) disrupts topology. A new stratified connected tree algorithm optimizes node locations, improving monitoring quality, connectivity, and network lifetime while minimizing node movement.

Keywords:

node redeployment self-examination and adjustment stratified connected tree underwater sensor networks

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Area of Science:

Computer Science
Network Engineering
Oceanography

Background:

Underwater sensor networks (UWSNs) face challenges due to node drift caused by water currents, leading to network topology changes.
Maintaining optimal network monitoring quality requires periodic node location examination and adjustments.

Purpose of the Study:

To propose a novel node redeployment algorithm for UWSNs to address topology changes caused by node drift.
To enhance network connectivity, coverage, and prolong network lifetime.

Main Methods:

A node redeployment algorithm based on a stratified connected tree structure is introduced.
Nodes perform self-examination and return to recorded locations if outside monitored space.
The sink node optimizes leaf node locations considering coverage, connectivity, and movement distance.

Main Results:

The algorithm effectively maintains a high number of nodes within the monitored space.
Good network coverage and connectivity rates are sustained during network operation.
Node movement distance during redeployment is reduced, extending overall network lifetime.

Conclusions:

The proposed algorithm successfully mitigates the effects of node drift in UWSNs.
It offers a balanced approach to maintaining network performance and operational efficiency.
This method is crucial for reliable long-term underwater monitoring applications.