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.
Highlights
Underwater wireless sensor networks (UWSNs) are underwater monitoring systems that comprise nodes with acoustic communication and computational capability [1]
The total distance moved in self-deployment depth adjustment algorithm (SDDA) is less than those in random uniform distributed algorithm (RAND) and connected dominating set (CDA), and slowly decreases as communication radius increases; the total distance moved in CTDA is the shortest
This study presents a distributed deployment algorithm based on connected tree (i.e., CTDA), where the sink node begins to build a connected tree as the first root node
Summary
Underwater wireless sensor networks (UWSNs) are underwater monitoring systems that comprise nodes with acoustic communication and computational capability [1]. We propose a distributed deployment algorithm by adjusting node positions vertically and building connected trees to maintain network connectivity. This algorithm, which is called a depth adjustment algorithm based on connected tree (CTDA), minimizes coverage overlap between the root and child nodes in a sub-tree to improve network coverage. The self-deployment depth adjustment algorithm (SDDA) [21] in terms of network coverage, connectivity, and deployment energy consumption under different node sensing ranges, communication ranges, and numbers of nodes. The simulation results show that CTDA always maintains high network connectivity under different communication ranges and numbers of nodes, while achieving high network coverage similar to that of SDDA under different sensing ranges and numbers of nodes but with less deployment energy consumption.
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