Next Article in Journal
An Assessment of Three Different In Situ Oxygen Sensors for Monitoring Silage Production and Storage
Next Article in Special Issue
A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms
Previous Article in Journal
Overview of Fiber Optic Sensor Technologies for Strain/Temperature Sensing Applications in Composite Materials
Previous Article in Special Issue
A New Node Deployment and Location Dispatch Algorithm for Underwater Sensor Networks
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(1), 98;

Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks

1,2,* , 1,2
College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou 310018, China
Author to whom correspondence should be addressed.
Academic Editor: Jaime Lloret Mauri
Received: 21 November 2015 / Revised: 6 January 2016 / Accepted: 7 January 2016 / Published: 14 January 2016
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Full-Text   |   PDF [4842 KB, uploaded 14 January 2016]   |  


Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption. View Full-Text
Keywords: node self-deployment; uneven clustering; radius adjusting; network reliability node self-deployment; uneven clustering; radius adjusting; network reliability

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Jiang, P.; Xu, Y.; Wu, F. Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks. Sensors 2016, 16, 98.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top