A Deployment Optimization Mechanism Using Depth Adjustable Nodes in Underwater Acoustic Sensor Networks

Jin, Zhigang; Ji, Zhihua; Su, Yishan; Li, Shuo; Wei, Bo

doi:10.1109/oceanskobe.2018.8559144

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…However, there are also few works that considered a 3D model for the underwater network. For instance, authors in [17] proposed a 3D network that is built by depth-adjustable nodes, i.e. every node can choose its depth freely.…”

Section: A Related Workmentioning

confidence: 99%

Coverage Enhancement of Underwater Internet of Things Using Multilevel Acoustic Communication Networks

Kishk

Alouini

2022

IEEE Internet Things J.

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Underwater acoustic communication networks (UACNs) are considered a key-enabler to the underwater internet of things (UIoT). UACN is regarded as essential for various marine applications such as monitoring, exploration, and trading. However, a large part of existing literature disregards the 3-dimensional (3D) nature of the underwater communication system. In this paper, we propose a K-tier UACN that acts as a gateway that connects the UIoT with the Space-Air-Ground-Sea Integrated System (SAGSIS). The proposed network architecture consists of several tiers along the vertical direction with adjustable depths. On the horizontal dimension, the best coverage probability (CP) is computed and maximized by optimizing the densities of surface stations (SSs) in each tier. On the vertical dimension, the depth of each tier is also optimized to minimize inter-tier interference and maximize overall system performance. Using tools from stochastic geometry, the total CP of the proposed K-tier network is analyzed. For given spatial distribution of UIoT device's depth, the best CP can be achieved by optimizing the depths of the transceivers connected to the SSs through a tether. We verify the accuracy of the analysis using Monte-Carlo simulations. In addition, we draw multiple useful system-level insights that help optimize the design of underwater 3D networks based on the given distribution of UIoT device's depths.

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Section: A Related Workmentioning

confidence: 99%

Coverage Enhancement of Underwater Internet of Things Using Multilevel Acoustic Communication Networks

Kishk

Alouini

2022

IEEE Internet Things J.

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“…UWSN is one of the promising research area and many of the researchers are working to explore about efficient node deployment 16,17,18 …”

Section: Related Workmentioning

confidence: 99%

“…UWSN is one of the promising research area and many of the researchers are working to explore about efficient node deployment. 16,17,18 Javaid et al 9 suggested a forwarding-function based routing procedure for UWSNs that is iAMCTD. Unlike the prevailing depth-based acoustic procedures, the suggested procedure uses density of the whole network for various time-critical applications.…”

Section: Related Workmentioning

confidence: 99%

Dynamic topology control algorithm for node deployment in mobile underwater wireless sensor networks

Choudhary

Goyal

2022

Concurrency and Computation

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Sensors in underwater wireless sensor networks (UWSNs) can drift up to 3 m/s due to ocean currents, marine organisms, or passing vessels. In existing node deployment and localization techniques, node mobility and network disconnections are not taken into account. This article proposes a dynamic topology control algorithm for node deployment (DTCND) in mobile UWSN. This work aims to monitor the node mobility to predict nodes' location for ensuring coverage and connectivity. The sensor nodes are deployed randomly at different depths. The anchor nodes observe the signal quality index, energy drain rate, and node density at every time interval and detect node disconnections based on the variations in these observed metrics. After receiving the beacon messages from the anchor nodes, the courier nodes incline to move toward the target region for satisfying the coverage and connectivity constraints. Simulation results show that the proposed algorithm attains 5% higher connectivity when compared to energy-efficient localization algorithm (EELA) and 9% higher connectivity when compared to adaptive triangular deployment algorithm (ATDA). The residual energy is also higher by 3% and 18% when compared to EELA and ATDA, respectively.The deployment cost and delay of DTCND also decrease when compared to EELA and ATDA, which results into efficient data collection.

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“…Moreover, it does not consider the issue of energy balance and energy holes. Jin et al [ 30 ] proposed a deployment optimization algorithm using depth adjustable nodes in underwater acoustic networks (DODA). This algorithm considers node drift situations when optimizing the node position.…”

Section: Related Researchmentioning

confidence: 99%

“…This algorithm strives to obtain the optimal network coverage rate on the basis of ensuring energy consumption balance and connectivity. Different from the recent approaches in the literature such as CDA [ 26 , 27 ], Cacc [ 28 ], VODA [ 29 ], and DODA [ 30 ], the proposed algorithm searches the global optimal dive position based on the basic nodes for depth calculation rather than the local optimal dive position. Furthermore, the proposed depth calculation method is with the goal of comprehensive optimization of both maximizing coverage utilization and energy balance, rather than just coverage only.…”

Section: Introductionmentioning

confidence: 99%

An Uneven Node Self-Deployment Optimization Algorithm for Maximized Coverage and Energy Balance in Underwater Wireless Sensor Networks

Yan

Huangfu

2021

Sensors

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The underwater wireless sensor networks (UWSNs) have been applied in lots of fields such as environment monitoring, military surveillance, data collection, etc. Deployment of sensor nodes in 3D UWSNs is a crucial issue, however, it is a challenging problem due to the complex underwater environment. This paper proposes a growth ring style uneven node depth-adjustment self-deployment optimization algorithm (GRSUNDSOA) to improve the coverage and reliability of UWSNs, meanwhile, and to solve the problem of energy holes. In detail, a growth ring style-based scheme is proposed for constructing the connective tree structure of sensor nodes and a global optimal depth-adjustment algorithm with the goal of comprehensive optimization of both maximizing coverage utilization and energy balance is proposed. Initially, the nodes are scattered to the water surface to form a connected network on this 2D plane. Then, starting from sink node, a growth ring style increment strategy is presented to organize the common nodes as tree structures and each root of subtree is determined. Meanwhile, with the goal of global maximizing coverage utilization and energy balance, all nodes depths are computed iteratively. Finally, all the nodes dive to the computed position once and a 3D underwater connected network with non-uniform distribution and balanced energy is constructed. A series of simulation experiments are performed. The simulation results show that the coverage and reliability of UWSN are improved greatly under the condition of full connectivity and energy balance, and the issue of energy hole can be avoided effectively. Therefore, GRSUNDSOA can prolong the lifetime of UWSN significantly.

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A Deployment Optimization Mechanism Using Depth Adjustable Nodes in Underwater Acoustic Sensor Networks

Cited by 9 publications

References 9 publications

Coverage Enhancement of Underwater Internet of Things Using Multilevel Acoustic Communication Networks

Coverage Enhancement of Underwater Internet of Things Using Multilevel Acoustic Communication Networks

Dynamic topology control algorithm for node deployment in mobile underwater wireless sensor networks

An Uneven Node Self-Deployment Optimization Algorithm for Maximized Coverage and Energy Balance in Underwater Wireless Sensor Networks

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