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Special Issue "Advances and Challenges in Underwater Sensor Networks"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 1 November 2017

Special Issue Editor

Guest Editor
Dr. Jaime Lloret Mauri

Integrated Management Coastal Research Institute, Polytechnic University of Valencia, Camino de Vera 46022, Valencia, Spain
Website | E-Mail
Fax: +34 96 2849313
Interests: wireless sensor networks; wireless local area networks; routing protocols; P2P networks; video streaming

Special Issue Information

Dear Colleagues,

Sensor technology is increasing by leaps and bounds. Today we can find smaller and more powerful sensor devices than few time ago. In some cases even cheaper. This fact allows the development of cheaper infrastructures for underwater monitoring, a wider range of underwater monitoring applications, the inclusion of more parameters for the observation of aquatic plants, fish or seafood, and the implementation of more complex data adquisition systems. Cheaper devices with better features facilitate the deployment of underwater sensor networks for coral reef conservation, aquaculture precision implementation and and sea pollution monitoring. More than 70% of the Earth is covered by water (about 97% of all the Earth's water is contained within the oceans as salt water), so there is a huge underwater environment to discover and research which needs new sensors and sensor networks. Moreover, there are multiple ways to communicate wired and wireless including acoustic, optical and Radio Frequency (RF) communications.

You are welcome to submit an original unpublished work related with underwater sensor nodes and underwater sensor networks.

Dr. Jaime Lloret
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • underwater sensors
  • underwater sensor nodes
  • underwater sensor networks
  • underwater monitoring
  • underwater surveillance

Published Papers (13 papers)

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Research

Open AccessArticle Probability-Based Recognition Framework for Underwater Landmarks Using Sonar Images
Sensors 2017, 17(9), 1953; doi:10.3390/s17091953
Received: 5 July 2017 / Revised: 18 August 2017 / Accepted: 21 August 2017 / Published: 24 August 2017
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Abstract
This paper proposes a probability-based framework for recognizing underwater landmarks using sonar images. Current recognition methods use a single image, which does not provide reliable results because of weaknesses of the sonar image such as unstable acoustic source, many speckle noises, low resolution
[...] Read more.
This paper proposes a probability-based framework for recognizing underwater landmarks using sonar images. Current recognition methods use a single image, which does not provide reliable results because of weaknesses of the sonar image such as unstable acoustic source, many speckle noises, low resolution images, single channel image, and so on. However, using consecutive sonar images, if the status—i.e., the existence and identity (or name)—of an object is continuously evaluated by a stochastic method, the result of the recognition method is available for calculating the uncertainty, and it is more suitable for various applications. Our proposed framework consists of three steps: (1) candidate selection, (2) continuity evaluation, and (3) Bayesian feature estimation. Two probability methods—particle filtering and Bayesian feature estimation—are used to repeatedly estimate the continuity and feature of objects in consecutive images. Thus, the status of the object is repeatedly predicted and updated by a stochastic method. Furthermore, we develop an artificial landmark to increase detectability by an imaging sonar, which we apply to the characteristics of acoustic waves, such as instability and reflection depending on the roughness of the reflector surface. The proposed method is verified by conducting basin experiments, and the results are presented. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle A Novel Cross-Layer Routing Protocol Based on Network Coding for Underwater Sensor Networks
Sensors 2017, 17(8), 1821; doi:10.3390/s17081821
Received: 29 June 2017 / Revised: 4 August 2017 / Accepted: 6 August 2017 / Published: 8 August 2017
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Abstract
Underwater wireless sensor networks (UWSNs) have attracted increasing attention in recent years because of their numerous applications in ocean monitoring, resource discovery and tactical surveillance. However, the design of reliable and efficient transmission and routing protocols is a challenge due to the low
[...] Read more.
Underwater wireless sensor networks (UWSNs) have attracted increasing attention in recent years because of their numerous applications in ocean monitoring, resource discovery and tactical surveillance. However, the design of reliable and efficient transmission and routing protocols is a challenge due to the low acoustic propagation speed and complex channel environment in UWSNs. In this paper, we propose a novel cross-layer routing protocol based on network coding (NCRP) for UWSNs, which utilizes network coding and cross-layer design to greedily forward data packets to sink nodes efficiently. The proposed NCRP takes full advantages of multicast transmission and decode packets jointly with encoded packets received from multiple potential nodes in the entire network. The transmission power is optimized in our design to extend the life cycle of the network. Moreover, we design a real-time routing maintenance protocol to update the route when detecting inefficient relay nodes. Substantial simulations in underwater environment by Network Simulator 3 (NS-3) show that NCRP significantly improves the network performance in terms of energy consumption, end-to-end delay and packet delivery ratio compared with other routing protocols for UWSNs. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Monocular Vision-Based Underwater Object Detection
Sensors 2017, 17(8), 1784; doi:10.3390/s17081784
Received: 24 May 2017 / Revised: 25 July 2017 / Accepted: 31 July 2017 / Published: 3 August 2017
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Abstract
In this paper, we propose an underwater object detection method using monocular vision sensors. In addition to commonly used visual features such as color and intensity, we investigate the potential of underwater object detection using light transmission information. The global contrast of various
[...] Read more.
In this paper, we propose an underwater object detection method using monocular vision sensors. In addition to commonly used visual features such as color and intensity, we investigate the potential of underwater object detection using light transmission information. The global contrast of various features is used to initially identify the region of interest (ROI), which is then filtered by the image segmentation method, producing the final underwater object detection results. We test the performance of our method with diverse underwater datasets. Samples of the datasets are acquired by a monocular camera with different qualities (such as resolution and focal length) and setups (viewing distance, viewing angle, and optical environment). It is demonstrated that our ROI detection method is necessary and can largely remove the background noise and significantly increase the accuracy of our underwater object detection method. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs
Sensors 2017, 17(8), 1762; doi:10.3390/s17081762
Received: 21 May 2017 / Revised: 13 July 2017 / Accepted: 26 July 2017 / Published: 1 August 2017
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Abstract
Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the
[...] Read more.
Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Cross Deployment Networking and Systematic Performance Analysis of Underwater Wireless Sensor Networks
Sensors 2017, 17(7), 1619; doi:10.3390/s17071619
Received: 5 May 2017 / Revised: 27 June 2017 / Accepted: 7 July 2017 / Published: 12 July 2017
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Abstract
Underwater wireless sensor networks (UWSNs) have become a new hot research area. However, due to the work dynamics and harsh ocean environment, how to obtain an UWSN with the best systematic performance while deploying as few sensor nodes as possible and setting up
[...] Read more.
Underwater wireless sensor networks (UWSNs) have become a new hot research area. However, due to the work dynamics and harsh ocean environment, how to obtain an UWSN with the best systematic performance while deploying as few sensor nodes as possible and setting up self-adaptive networking is an urgent problem that needs to be solved. Consequently, sensor deployment, networking, and performance calculation of UWSNs are challenging issues, hence the study in this paper centers on this topic and three relevant methods and models are put forward. Firstly, the normal body-centered cubic lattice to cross body-centered cubic lattice (CBCL) has been improved, and a deployment process and topology generation method are built. Then most importantly, a cross deployment networking method (CDNM) for UWSNs suitable for the underwater environment is proposed. Furthermore, a systematic quar-performance calculation model (SQPCM) is proposed from an integrated perspective, in which the systematic performance of a UWSN includes coverage, connectivity, durability and rapid-reactivity. Besides, measurement models are established based on the relationship between systematic performance and influencing parameters. Finally, the influencing parameters are divided into three types, namely, constraint parameters, device performance and networking parameters. Based on these, a networking parameters adjustment method (NPAM) for optimized systematic performance of UWSNs has been presented. The simulation results demonstrate that the approach proposed in this paper is feasible and efficient in networking and performance calculation of UWSNs. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle A Noise Removal Method for Uniform Circular Arrays in Complex Underwater Noise Environments with Low SNR
Sensors 2017, 17(6), 1345; doi:10.3390/s17061345
Received: 19 April 2017 / Revised: 6 June 2017 / Accepted: 6 June 2017 / Published: 9 June 2017
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Abstract
Generally, many beamforming methods are derived under the assumption of white noise. In practice, the actual underwater ambient noise is complex. As a result, the noise removal capacity of the beamforming method may be deteriorated considerably. Furthermore, in underwater environment with extremely low
[...] Read more.
Generally, many beamforming methods are derived under the assumption of white noise. In practice, the actual underwater ambient noise is complex. As a result, the noise removal capacity of the beamforming method may be deteriorated considerably. Furthermore, in underwater environment with extremely low signal-to-noise ratio (SNR), the performances of the beamforming method may be deteriorated. To tackle these problems, a noise removal method for uniform circular array (UCA) is proposed to remove the received noise and improve the SNR in complex noise environments with low SNR. First, the symmetrical noise sources are defined and the spatial correlation of the symmetrical noise sources is calculated. Then, based on the preceding results, the noise covariance matrix is decomposed into symmetrical and asymmetrical components. Analysis indicates that the symmetrical component only affect the real part of the noise covariance matrix. Consequently, the delay-and-sum (DAS) beamforming is performed by using the imaginary part of the covariance matrix to remove the symmetrical component. However, the noise removal method causes two problems. First, the proposed method produces a false target. Second, the proposed method would seriously suppress the signal when it is located in some directions. To solve the first problem, two methods to reconstruct the signal covariance matrix are presented: based on the estimation of signal variance and based on the constrained optimization algorithm. To solve the second problem, we can design the array configuration and select the suitable working frequency. Theoretical analysis and experimental results are included to demonstrate that the proposed methods are particularly effective in complex noise environments with low SNR. The proposed method can be extended to any array. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle A Double Rate Localization Algorithm with One Anchor for Multi-Hop Underwater Acoustic Networks
Sensors 2017, 17(5), 984; doi:10.3390/s17050984
Received: 25 January 2017 / Revised: 24 April 2017 / Accepted: 25 April 2017 / Published: 28 April 2017
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Abstract
Localization is a basic issue for underwater acoustic networks (UANs). Currently, most localization algorithms only perform well in one-hop networks or need more anchors which are not suitable for the underwater environment. In this paper, we proposed a double rate localization algorithm with
[...] Read more.
Localization is a basic issue for underwater acoustic networks (UANs). Currently, most localization algorithms only perform well in one-hop networks or need more anchors which are not suitable for the underwater environment. In this paper, we proposed a double rate localization algorithm with one anchor for multi-hop underwater acoustic networks (DRL). The algorithm firstly presents a double rate scheme which separates the localization procedure into two modes to increase the ranging accuracy in multi-hop UANs while maintaining the transmission rate. Then an optimal selection scheme of reference nodes was proposed to reduce the influence of references’ topology on localization performance. The proposed DRL algorithm can be used in the multi-hop UANs to increase the localization accuracy and reduce the usage of anchor nodes. The simulation and experimental results demonstrated that the proposed DRL algorithm has a better localization performance than the previous algorithms in many aspects such as accuracy and communication cost, and is more suitable to the underwater environment. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks
Sensors 2017, 17(5), 971; doi:10.3390/s17050971
Received: 21 March 2017 / Revised: 19 April 2017 / Accepted: 23 April 2017 / Published: 27 April 2017
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Abstract
We study the problem of energy-efficient target tracking in underwater wireless sensor networks (UWSNs). Since sensors of UWSNs are battery-powered, it is impracticable to replace the batteries when exhausted. This means that the battery life affects the lifetime of the whole network. In
[...] Read more.
We study the problem of energy-efficient target tracking in underwater wireless sensor networks (UWSNs). Since sensors of UWSNs are battery-powered, it is impracticable to replace the batteries when exhausted. This means that the battery life affects the lifetime of the whole network. In order to extend the network lifetime, it is worth reducing the energy consumption on the premise of sufficient tracking accuracy. This paper proposes an energy-efficient filter that implements the tradeoff between communication cost and tracking accuracy. Under the distributed fusion framework, local sensors should not send their weak information to the fusion center if their measurement residuals are smaller than the pre-given threshold. In order to guarantee the target tracking accuracy, artificial measurements are generated to compensate for those unsent real measurements. Then, an adaptive scheme is derived to take full advantages of the artificial measurements-based filter in terms of energy-efficiency. Furthermore, a computationally efficient optimal sensor selection scheme is proposed to improve tracking accuracy on the premise of employing the same number of sensors. Simulation demonstrates that our scheme has superior advantages in the tradeoff between communication cost and tracking accuracy. It saves much energy while loosing little tracking accuracy or improves tracking performance with less additional energy cost. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Energy-Efficient Channel Coding Strategy for Underwater Acoustic Networks
Sensors 2017, 17(4), 728; doi:10.3390/s17040728
Received: 20 December 2016 / Revised: 22 March 2017 / Accepted: 24 March 2017 / Published: 31 March 2017
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Abstract
Underwater acoustic networks (UAN) allow for efficiently exploiting and monitoring the sub-aquatic environment. These networks are characterized by long propagation delays, error-prone channels and half-duplex communication. In this paper, we address the problem of energy-efficient communication through the use of optimized channel coding
[...] Read more.
Underwater acoustic networks (UAN) allow for efficiently exploiting and monitoring the sub-aquatic environment. These networks are characterized by long propagation delays, error-prone channels and half-duplex communication. In this paper, we address the problem of energy-efficient communication through the use of optimized channel coding parameters. We consider a two-layer encoding scheme employing forward error correction (FEC) codes and fountain codes (FC) for UAN scenarios without feedback channels. We model and evaluate the energy consumption of different channel coding schemes for a K-distributed multipath channel. The parameters of the FEC encoding layer are optimized by selecting the optimal error correction capability and the code block size. The results show the best parameter choice as a function of the link distance and received signal-to-noise ratio. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks
Sensors 2017, 17(4), 726; doi:10.3390/s17040726
Received: 6 January 2017 / Revised: 24 March 2017 / Accepted: 27 March 2017 / Published: 30 March 2017
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Abstract
Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of
[...] Read more.
Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Node Self-Deployment Algorithm Based on Pigeon Swarm Optimization for Underwater Wireless Sensor Networks
Sensors 2017, 17(4), 674; doi:10.3390/s17040674
Received: 19 January 2017 / Revised: 20 March 2017 / Accepted: 20 March 2017 / Published: 24 March 2017
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Abstract
At present, free-to-move node self-deployment algorithms aim at event coverage and cannot improve network coverage under the premise of considering network connectivity, network reliability and network deployment energy consumption. Thus, this study proposes pigeon-based self-deployment algorithm (PSA) for underwater wireless sensor networks to
[...] Read more.
At present, free-to-move node self-deployment algorithms aim at event coverage and cannot improve network coverage under the premise of considering network connectivity, network reliability and network deployment energy consumption. Thus, this study proposes pigeon-based self-deployment algorithm (PSA) for underwater wireless sensor networks to overcome the limitations of these existing algorithms. In PSA, the sink node first finds its one-hop nodes and maximizes the network coverage in its one-hop region. The one-hop nodes subsequently divide the network into layers and cluster in each layer. Each cluster head node constructs a connected path to the sink node to guarantee network connectivity. Finally, the cluster head node regards the ratio of the movement distance of the node to the change in the coverage redundancy ratio as the target function and employs pigeon swarm optimization to determine the positions of the nodes. Simulation results show that PSA improves both network connectivity and network reliability, decreases network deployment energy consumption, and increases network coverage. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Cooperative Position Aware Mobility Pattern of AUVs for Avoiding Void Zones in Underwater WSNs
Sensors 2017, 17(3), 580; doi:10.3390/s17030580
Received: 2 January 2017 / Revised: 2 March 2017 / Accepted: 7 March 2017 / Published: 13 March 2017
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Abstract
In this paper, we propose two schemes; position-aware mobility pattern (PAMP) and cooperative PAMP (Co PAMP). The first one is an optimization scheme that avoids void hole occurrence and minimizes the uncertainty in the position estimation of glider’s. The second one is a
[...] Read more.
In this paper, we propose two schemes; position-aware mobility pattern (PAMP) and cooperative PAMP (Co PAMP). The first one is an optimization scheme that avoids void hole occurrence and minimizes the uncertainty in the position estimation of glider’s. The second one is a cooperative routing scheme that reduces the packet drop ratio by using the relay cooperation. Both techniques use gliders that stay at sojourn positions for a predefined time, at sojourn position self-confidence (s-confidence) and neighbor-confidence (n-confidence) regions that are estimated for balanced energy consumption. The transmission power of a glider is adjusted according to those confidence regions. Simulation results show that our proposed schemes outperform the compared existing one in terms of packet delivery ratio, void zones and energy consumption. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Probabilistic Neighborhood-Based Data Collection Algorithms for 3D Underwater Acoustic Sensor Networks
Sensors 2017, 17(2), 316; doi:10.3390/s17020316
Received: 9 January 2017 / Revised: 6 February 2017 / Accepted: 6 February 2017 / Published: 8 February 2017
PDF Full-text (593 KB) | HTML Full-text | XML Full-text
Abstract
Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information
[...] Read more.
Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information conveniently, efficiently and accurately. However, the specific propagation effects of acoustic communication channel lead to decreased successful information delivery probability with increased distance. Therefore, we investigate two probabilistic neighborhood-based data collection algorithms for 3D UASNs which are based on a probabilistic acoustic communication model instead of the traditional deterministic acoustic communication model. An autonomous underwater vehicle (AUV) is employed to traverse along the designed path to collect data from neighborhoods. For 3D UASNs without prior deployment knowledge, partitioning the network into grids can allow the AUV to visit the central location of each grid for data collection. For 3D UASNs in which the deployment knowledge is known in advance, the AUV only needs to visit several selected locations by constructing a minimum probabilistic neighborhood covering set to reduce data latency. Otherwise, by increasing the transmission rounds, our proposed algorithms can provide a tradeoff between data collection latency and information gain. These algorithms are compared with basic Nearest-neighbor Heuristic algorithm via simulations. Simulation analyses show that our proposed algorithms can efficiently reduce the average data collection completion time, corresponding to a decrease of data latency. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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