A hybrid coverage control for enhancing UWSN localizability using IBSO-VFA

Luo, Chengming; Wang, Biao; Cao, Yuxin; Xin, Gaifang; He, Cheng; Ma, Lin

doi:10.1016/j.adhoc.2021.102694

Cited by 18 publications

(9 citation statements)

References 28 publications

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“…In UWSNs, the underwater nodes are affected by environmental factors such as underwater currents, tides, and wind, and their positions change, to some extent [31]. Therefore, it is crucial to analyze the movement of underwater nodes.…”

Section: Coverage Description and Node Motion Modelmentioning

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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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: Coverage Description and Node Motion Modelmentioning

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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“…Underwater visual imaging can be obtained by using a visual sensor installed on a remotely operated vehicle (ROV), which has characteristics of wide spectral sensitivity range and rich visual perceptual information [6,7]. Furthermore, the location of the detected dam defects inspected by a visual sensor can be marked by the real-time acoustic positioning of the ROV [8,9]. However, underwater measurement is readily subject to interference by the complex environment and quantization noise [10].…”

Section: Problem Statementmentioning

confidence: 99%

A fine extraction algorithm for image-based surface cracks in underwater dams

Xin¹,

Fan²,

Shi³

et al. 2022

Meas. Sci. Technol.

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Under the action of water erosion and self-aging action, reservoir dams are prone to have cracks, affecting the safe operation. Underwater visual imaging can be used to detect dam surface cracks, but the spalling, aquatic plants and suspended sediments result in low image contrast and complex backgrounds. With the use of unsupervised machine learning, this paper proposes a fine segmentation and extraction algorithm for image-based dam surface cracks. Firstly, the adaptive histogram equalization is used to make the uneven illumination areas of underwater surface images be even illumination areas, whose statistical characteristics is calculated under the linear spatial filtering. Secondly, the extraction problem of interested crack areas after dodging preprocess is transformed into calculating the distance of image block cluster center, which can distinguish the image blocks of crack features from the background interference features. Thirdly, the fine extraction of crack images is carried out in consideration of the connected domains and morphological features, and the posterior probability of image sample category is obtained based on the soft clustering of Gaussian mixed model. Finally, different extraction algorithms related to surface cracks are evaluated in extensive experiments. The results validate the superior performance of the proposed extraction algorithm with 90.1% extraction accuracy, 6.5% missing alarm rate, and 7.2% false alarm rate.

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“…MCOBR [23]: To address the concerns of multi-path fading, low throughput, sinkhole, etc. the authors proposed the MCBOR algorithm.…”

Section: Related Workmentioning

confidence: 99%

SC 2 R: Strategic cooperative cluster-based routing for Internet of Underwater Things

Gupta

Singh

2022

Preprint

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Oceanographic data gathering, pollution monitoring, offshore exploration, catastrophe avoidance, aided navigation, and tactical surveillance are all expected to benefit from the Internet of Underwater Things (IoUT). However, the viability of various applications in underwater scenarios is possible only if the routing among the sensor nodes employed is strategically optimized. This paper proposes Strategic Cooperative Routing for IoUT (SC2R) that employs a cooperative node for data collection from each Cluster-Head (CH). CH selection is done through the energy and distance parameters. The cooperative nodes are positioned on water surface, other nodes being placed in the underwater terrain. This cooperative routing helps in the data collection for the time-critical scenario as it avoids multi-hop communication among the sensor nodes underwater. Due to decreased number of hops of communication, the delay in data transmission is reduced. The simulation results illustrate the efficacy of the proposed routing technique in comparison to competitive algorithms. The proposed protocol outperforms state of art routing protocols in terms of Network Lifetime and End to End Delay (EED).

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A hybrid coverage control for enhancing UWSN localizability using IBSO-VFA

Cited by 18 publications

References 28 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

A fine extraction algorithm for image-based surface cracks in underwater dams

SC 2 R: Strategic cooperative cluster-based routing for Internet of Underwater Things

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