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Sensors 2015, 15(7), 16763-16785; doi:10.3390/s150716763

Node Deployment Algorithm Based on Connected Tree for Underwater Sensor Networks

1
Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Hangzhou 310018, China
2
School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 30 April 2015 / Revised: 17 June 2015 / Accepted: 6 July 2015 / Published: 10 July 2015
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [953 KB, uploaded 10 July 2015]   |  

Abstract

Designing an efficient deployment method to guarantee optimal monitoring quality is one of the key topics in underwater sensor networks. At present, a realistic approach of deployment involves adjusting the depths of nodes in water. One of the typical algorithms used in such process is the self-deployment depth adjustment algorithm (SDDA). This algorithm mainly focuses on maximizing network coverage by constantly adjusting node depths to reduce coverage overlaps between two neighboring nodes, and thus, achieves good performance. However, the connectivity performance of SDDA is irresolute. In this paper, we propose a depth adjustment algorithm based on connected tree (CTDA). In CTDA, the sink node is used as the first root node to start building a connected tree. Finally, the network can be organized as a forest to maintain network connectivity. Coverage overlaps between the parent node and the child node are then reduced within each sub-tree to optimize coverage. The hierarchical strategy is used to adjust the distance between the parent node and the child node to reduce node movement. Furthermore, the silent mode is adopted to reduce communication cost. Simulations show that compared with SDDA, CTDA can achieve high connectivity with various communication ranges and different numbers of nodes. Moreover, it can realize coverage as high as that of SDDA with various sensing ranges and numbers of nodes but with less energy consumption. Simulations under sparse environments show that the connectivity and energy consumption performances of CTDA are considerably better than those of SDDA. Meanwhile, the connectivity and coverage performances of CTDA are close to those depth adjustment algorithms base on connected dominating set (CDA), which is an algorithm similar to CTDA. However, the energy consumption of CTDA is less than that of CDA, particularly in sparse underwater environments. View Full-Text
Keywords: underwater sensor network deployment; node depth adjustment; 3D coverage; connected tree underwater sensor network deployment; node depth adjustment; 3D coverage; connected tree
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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).

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Jiang, P.; Wang, X.; Jiang, L. Node Deployment Algorithm Based on Connected Tree for Underwater Sensor Networks. Sensors 2015, 15, 16763-16785.

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