Sensor Deployment Strategies for Target Coverage Problems in Underwater Acoustic Sensor Networks

Yi, Jinwang; Qiao, Guanhao; Yuan, Fei; Tian, Yue; Wang, Xianling

doi:10.1109/lcomm.2023.3237718

Cited by 12 publications

(3 citation statements)

References 10 publications

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“…As the water moves, the nodes change position, making UWSNs prone to dynamic topology drifts. To solve the coverage problem in an underwater dynamic environment and with depth information as the preferred selection condition, the optimal deployment was selected using a strategy of obtaining the optimal solution step by step; this was also effective for irregularly distributed underwater nodes [17]. To directly improve the global search capability for obtaining global optimal coverage, Zhang et al utilized an enhanced fruit fly optimization algorithm to reasonably adjust node positions [18].…”

Section: Introductionmentioning

confidence: 99%

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Three-Dimensional Iterative Enhancement for Coverage Hole Recovery in Underwater Wireless Sensor Networks

Zhang,

Luo,

et al. 2023

JMSE

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The efficient coverage of underwater wireless sensor networks (UWSNs) has become increasingly important because of the scarcity of underwater node resources. Complex underwater environments, water flow forces, and undulating seabed reduce the coverage effect of underwater nodes, even leading to coverage holes in UWSNs. To solve the problems of uneven coverage distribution and coverage holes, a three-dimensional iterative enhancement algorithm is proposed for UWSN coverage hole recovery using intelligent search followed by virtual force. Benefiting from biological heuristic search algorithms, improved particle swarm optimization is applied for node pre-coverage. With the change in iteration times, the adaptive inertia weight, acceleration factor, and node position are constantly updated. To avoid excessive coverage holes caused by search falling into local optimum, underwater nodes are considered as particles in the potential field whose virtual forces are calculated to guide nodes towards higher coverage positions. In addition, based on the optimal node location obtained by the proposed algorithm, the monitoring area is divided based on the clustering idea. The underwater routing protocol DBR based on depth information is subsequently used to optimize node residual energy, and its average is calculated comprehensively and compared with the other three coverage algorithms using the DBR routing protocol. Based on the experimental data, after 100 iterations, the coverage rates for BES, 3D-IVFA, DABVF, and the proposed algorithm are 83.28%, 88.85%, 89.31%, and 91.36%, respectively. Moreover, the proposed algorithm is further verified from the aspects of different node numbers, coverage efficiency, node movement trajectory, coverage hole, and average residual energy of nodes, which provides conditions for resource development and scientific research in marine environments.

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Section: Introductionmentioning

confidence: 99%

“…Zhao, X.Q., 2019 [16] VBO Energy consumption Multi-energy optimization during redeployment. Yi, J., 2023 [17] IGS Node coverage Transform coverage problem into multiple local optimal. Zhang, Y., 2017 [18] UFOA Node coverage Optimal coverage under drosophila foraging behavior.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Iterative Enhancement for Coverage Hole Recovery in Underwater Wireless Sensor Networks

Zhang,

Luo,

et al. 2023

JMSE

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“…Through collaborative work between nodes, various environmental monitoring and sensing information can be transmitted to the BS in real-time. If a large quantity of nodes is thrown randomly in reasonable locations, they can cover the target area more precisely [5,6]. However, in real target scenarios, it is often required to throw nodes randomly in a high-density, large-scale manner in sensor networks, but this large-scale random node-throwing approach makes it difficult to deploy nodes in optimal locations at once, resulting in redundant and unperceived regions due to either the over-sparse or dense distribution of nodes in the target region.…”

Section: Introductionmentioning

confidence: 99%

DHD-MEPO: A Novel Distributed Coverage Hole Detection and Repair Method for Three-Dimensional Hybrid Wireless Sensor Networks

Gou

Guo

et al. 2023

Electronics

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A coverage hole is a problem that cannot be completely avoided in three-dimensional hybrid wireless sensor networks. It can lead to hindrances in monitoring tasks and adversely affect network performance. To address the problem of coverage holes caused by the uneven initial deployment of the network and node damage during operation, we propose a distributed hole detection and multi-objective optimization emperor penguin repair algorithm (DHD-MEPO). In the detection phase, the monitoring region is zoned as units according to the quantity of nodes and the sensing range, and static nodes use the sum-of-weights method to campaign for group nodes on their terms, determining the location of holes by calculating the coverage of each cell. In the repair phase, the set of repair nodes is determined by calculating the mobile node coverage redundancy. Based on the characteristics of complex environments, the regions of high hole levels are prioritized. Moreover, the residual energy homogeneity of nodes is considered for the design of multi-objective functions. A lens-imaging mapping learning strategy is introduced to perturb the location of repair nodes for the optimization of the emperor penguin algorithm. Experimental results illustrate that the DHD-MEPO, compared with the C-CICHH, 3D-VPCA, RA, EMSCOLER, and IERP algorithms, can balance the uniformity of the residual energy of each node while satisfying the network coverage requirements and network connectivity, which effectively improves the network coverage performance.

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Coverage and Connectivity Aware Deployment Scheme for Autonomous Underwater Vehicles in Underwater Wireless Sensor Networks

Kumari

Mishra

Anand

2023

Wireless Pers Commun

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Sensor Deployment Strategies for Target Coverage Problems in Underwater Acoustic Sensor Networks

Cited by 12 publications

References 10 publications

Three-Dimensional Iterative Enhancement for Coverage Hole Recovery in Underwater Wireless Sensor Networks

Three-Dimensional Iterative Enhancement for Coverage Hole Recovery in Underwater Wireless Sensor Networks

DHD-MEPO: A Novel Distributed Coverage Hole Detection and Repair Method for Three-Dimensional Hybrid Wireless Sensor Networks

Coverage and Connectivity Aware Deployment Scheme for Autonomous Underwater Vehicles in Underwater Wireless Sensor Networks

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