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Special Issue "Underwater Sensor Nodes and Underwater Sensor Networks 2016"

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

Deadline for manuscript submissions: closed (15 January 2016)

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,

Lakes, seas and oceans cover more than the 70% of the Earth surface. The miniaturization of the hardware, jointly from the efforts to develop low cost and low energy consumption devices, has brought new ways to sense and monitor marine environments. New research advances in underwater communication and sensing systems have increased both the types of network topologies to spread in the environment and the sensing parameters. However, new marine data collection and data fusion systems for marine surveillance and pollution detection are needed. Moreover, new schemes to explore and protect the marine environment are pursued to increase the number of applications, which can vary from fish and mussel grow observations, deep-sea archaeology, and seismic and volcanic prediction, to spilled oil monitoring.

This Special Issue welcomes works with recent advances on sensors and sensor networks to monitor, observe, measure, control, and manage underwater environments. Many aquatic environment features should be taken into account when designing and deploying underwater sensor nodes and networks, such as the scalability, to allow deploying large number of nodes, node power consumption and resource limitation, wireless underwater communication, propagation latency, high probability error rate, and bandwidth capacity. All these constraints given by an environment’s nature make underwater sensors and sensor networks a complex deployment and implementation case.

This Special Issue includes, but is not limited to, the following topics of interest:

  • Sensor devices to measure water parameters
  • Pollution sensor nodes
  • Sediment and seabed monitoring nodes
  • Underwater acoustic sensors
  • Underwater sensor architectures
  • Wired and wireless protocols
  • Localization and positioning systems
  • Underwater Target tracking
  • Optical, acoustic and electromagnetic underwater communications
  • Radiofrequency communications in underwater environments
  • Modems
  • Study cases, implementations and real deployments of underwater sensor networks
  • Routing protocols specialized for underwater wireless sensor networks
  • Cooperation in underwater sensor networks
  • Modeling and simulation
  • Data collection, data fusion, storage, and data retrieval

Recent advances in electronics, circuits, systems, communication protocols, network algorithms, and data mining have made possible new advances in underwater environments. They are the basis to propose new underwater wireless sensor nodes, sensor node location, sensor node placement, communication protocols, and network architectures, because they allow the study of new ways to communicate underwater with higher data rates with longer distances. Moreover, more underwater applications appear every year because these advances support investigations in marine biology, marine science, oceanography, aquiculture, and environment engineering research fields.

This Special Issue will include unpublished works related with theory and practice of underwater sensor nodes and networks, with special interest on practical implementations and deployments. We also seek new proposals on underwater wireless communication technologies.

Dr. Jaime Lloret Mauri
Guest Editor

Manuscript Submission Information

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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 sensor nodes
  • Underwater sensor node placement
  • UWSNs (Underwater Wireless Sensor Networks)
  • Routing protocols for underwater sensor networks
  • Underwater network architectures
  • Underwater wireless communications
  • Underwater sensor network deployments

Published Papers (23 papers)

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Research

Open AccessArticle RF Path and Absorption Loss Estimation for Underwater Wireless Sensor Networks in Different Water Environments
Sensors 2016, 16(6), 890; doi:10.3390/s16060890
Received: 13 February 2016 / Revised: 27 May 2016 / Accepted: 9 June 2016 / Published: 16 June 2016
Cited by 3 | PDF Full-text (526 KB) | HTML Full-text | XML Full-text
Abstract
Underwater Wireless Sensor Network (UWSN) communication at high frequencies is extremely challenging. The intricacies presented by the underwater environment are far more compared to the terrestrial environment. The prime reason for such intricacies are the physical characteristics of the underwater environment that have
[...] Read more.
Underwater Wireless Sensor Network (UWSN) communication at high frequencies is extremely challenging. The intricacies presented by the underwater environment are far more compared to the terrestrial environment. The prime reason for such intricacies are the physical characteristics of the underwater environment that have a big impact on electromagnetic (EM) signals. Acoustics signals are by far the most preferred choice for underwater wireless communication. Because high frequency signals have the luxury of large bandwidth (BW) at shorter distances, high frequency EM signals cannot penetrate and propagate deep in underwater environments. The EM properties of water tend to resist their propagation and cause severe attenuation. Accordingly, there are two questions that need to be addressed for underwater environment, first what happens when high frequency EM signals operating at 2.4 GHz are used for communication, and second which factors affect the most to high frequency EM signals. To answer these questions, we present real-time experiments conducted at 2.4 GHz in terrestrial and underwater (fresh water) environments. The obtained results helped in studying the physical characteristics (i.e., EM properties, propagation and absorption loss) of underwater environments. It is observed that high frequency EM signals can propagate in fresh water at a shallow depth only and can be considered for a specific class of applications such as water sports. Furthermore, path loss, velocity of propagation, absorption loss and the rate of signal loss in different underwater environments are also calculated and presented in order to understand why EM signals cannot propagate in sea water and oceanic water environments. An optimal solk6ution for underwater communication in terms of coverage distance, bandwidth and nature of communication is presented, along with possible underwater applications of UWSNs at 2.4 GHz. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Multibeam 3D Underwater SLAM with Probabilistic Registration
Sensors 2016, 16(4), 560; doi:10.3390/s16040560
Received: 15 January 2016 / Revised: 13 April 2016 / Accepted: 14 April 2016 / Published: 20 April 2016
Cited by 2 | PDF Full-text (9494 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM) using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point
[...] Read more.
This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM) using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds). An Iterative Closest Point (ICP) with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1) point-to-point association for coarse registration and (2) point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O ( n 2 ) to O ( n ) . The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks
Sensors 2016, 16(4), 525; doi:10.3390/s16040525
Received: 15 December 2015 / Revised: 26 February 2016 / Accepted: 8 March 2016 / Published: 12 April 2016
Cited by 5 | PDF Full-text (2800 KB) | HTML Full-text | XML Full-text
Abstract
Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data
[...] Read more.
Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
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Open AccessArticle Close-Range Tracking of Underwater Vehicles Using Light Beacons
Sensors 2016, 16(4), 429; doi:10.3390/s16040429
Received: 15 January 2016 / Revised: 5 March 2016 / Accepted: 18 March 2016 / Published: 25 March 2016
Cited by 5 | PDF Full-text (17571 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a new tracking system for autonomous underwater vehicles (AUVs) navigating in a close formation, based on computer vision and the use of active light markers. While acoustic localization can be very effective from medium to long distances, it is not
[...] Read more.
This paper presents a new tracking system for autonomous underwater vehicles (AUVs) navigating in a close formation, based on computer vision and the use of active light markers. While acoustic localization can be very effective from medium to long distances, it is not so advantageous in short distances when the safety of the vehicles requires higher accuracy and update rates. The proposed system allows the estimation of the pose of a target vehicle at short ranges, with high accuracy and execution speed. To extend the field of view, an omnidirectional camera is used. This camera provides a full coverage of the lower hemisphere and enables the concurrent tracking of multiple vehicles in different positions. The system was evaluated in real sea conditions by tracking vehicles in mapping missions, where it demonstrated robust operation during extended periods of time. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Monitoring Anthropogenic Ocean Sound from Shipping Using an Acoustic Sensor Network and a Compressive Sensing Approach
Sensors 2016, 16(3), 415; doi:10.3390/s16030415
Received: 12 January 2016 / Revised: 14 March 2016 / Accepted: 18 March 2016 / Published: 22 March 2016
Cited by 3 | PDF Full-text (844 KB) | HTML Full-text | XML Full-text
Abstract
Monitoring ocean acoustic noise has been the subject of considerable recent study, motivated by the desire to assess the impact of anthropogenic noise on marine life. A combination of measuring ocean sound using an acoustic sensor network and modelling sources of sound and
[...] Read more.
Monitoring ocean acoustic noise has been the subject of considerable recent study, motivated by the desire to assess the impact of anthropogenic noise on marine life. A combination of measuring ocean sound using an acoustic sensor network and modelling sources of sound and sound propagation has been proposed as an approach to estimating the acoustic noise map within a region of interest. However, strategies for developing a monitoring network are not well established. In this paper, considerations for designing a network are investigated using a simulated scenario based on the measurement of sound from ships in a shipping lane. Using models for the sources of the sound and for sound propagation, a noise map is calculated and measurements of the noise map by a sensor network within the region of interest are simulated. A compressive sensing algorithm, which exploits the sparsity of the representation of the noise map in terms of the sources, is used to estimate the locations and levels of the sources and thence the entire noise map within the region of interest. It is shown that although the spatial resolution to which the sound sources can be identified is generally limited, estimates of aggregated measures of the noise map can be obtained that are more reliable compared with those provided by other approaches. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle A Survey on Underwater Acoustic Sensor Network Routing Protocols
Sensors 2016, 16(3), 414; doi:10.3390/s16030414
Received: 4 February 2016 / Revised: 16 March 2016 / Accepted: 16 March 2016 / Published: 22 March 2016
Cited by 22 | PDF Full-text (1064 KB) | HTML Full-text | XML Full-text
Abstract
Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission
[...] Read more.
Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Validation of Underwater Sensor Package Using Feature Based SLAM
Sensors 2016, 16(3), 380; doi:10.3390/s16030380
Received: 14 December 2015 / Revised: 2 March 2016 / Accepted: 4 March 2016 / Published: 17 March 2016
Cited by 1 | PDF Full-text (2940 KB) | HTML Full-text | XML Full-text
Abstract
Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed
[...] Read more.
Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Underwater Multi-Vehicle Trajectory Alignment and Mapping Using Acoustic and Optical Constraints
Sensors 2016, 16(3), 387; doi:10.3390/s16030387
Received: 14 January 2016 / Revised: 3 March 2016 / Accepted: 4 March 2016 / Published: 17 March 2016
Cited by 3 | PDF Full-text (14027 KB) | HTML Full-text | XML Full-text
Abstract
Multi-robot formations are an important advance in recent robotic developments, as they allow a group of robots to merge their capacities and perform surveys in a more convenient way. With the aim of keeping the costs and acoustic communications to a minimum, cooperative
[...] Read more.
Multi-robot formations are an important advance in recent robotic developments, as they allow a group of robots to merge their capacities and perform surveys in a more convenient way. With the aim of keeping the costs and acoustic communications to a minimum, cooperative navigation of multiple underwater vehicles is usually performed at the control level. In order to maintain the desired formation, individual robots just react to simple control directives extracted from range measurements or ultra-short baseline (USBL) systems. Thus, the robots are unaware of their global positioning, which presents a problem for the further processing of the collected data. The aim of this paper is two-fold. First, we present a global alignment method to correct the dead reckoning trajectories of multiple vehicles to resemble the paths followed during the mission using the acoustic messages passed between vehicles. Second, we focus on the optical mapping application of these types of formations and extend the optimization framework to allow for multi-vehicle geo-referenced optical 3D mapping using monocular cameras. The inclusion of optical constraints is not performed using the common bundle adjustment techniques, but in a form improving the computational efficiency of the resulting optimization problem and presenting a generic process to fuse optical reconstructions with navigation data. We show the performance of the proposed method on real datasets collected within the Morph EU-FP7 project. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
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Open AccessArticle Node Deployment Algorithm for Underwater Sensor Networks Based on Connected Dominating Set
Sensors 2016, 16(3), 388; doi:10.3390/s16030388
Received: 27 January 2016 / Revised: 26 February 2016 / Accepted: 2 March 2016 / Published: 17 March 2016
Cited by 4 | PDF Full-text (1447 KB) | HTML Full-text | XML Full-text
Abstract
Existing node deployment algorithms for underwater sensor networks are nearly unable to improve the network coverage rate under the premise of ensuring the full network connectivity and do not optimize the communication and move energy consumption during the deployment. Hence, a node deployment
[...] Read more.
Existing node deployment algorithms for underwater sensor networks are nearly unable to improve the network coverage rate under the premise of ensuring the full network connectivity and do not optimize the communication and move energy consumption during the deployment. Hence, a node deployment algorithm based on connected dominating set (CDS) is proposed. After randomly sowing the nodes in 3D monitoring underwater space, disconnected nodes move to the sink node until the network achieves full connectivity. The sink node then performs centralized optimization to determine the CDS and adjusts the locations of dominated nodes. Simulation results show that the proposed algorithm can achieve a high coverage rate while ensuring full connectivity and decreases the communication and movement energy consumption during deployment. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle AUV Positioning Method Based on Tightly Coupled SINS/LBL for Underwater Acoustic Multipath Propagation
Sensors 2016, 16(3), 357; doi:10.3390/s16030357
Received: 20 January 2016 / Revised: 29 February 2016 / Accepted: 7 March 2016 / Published: 11 March 2016
Cited by 3 | PDF Full-text (3290 KB) | HTML Full-text | XML Full-text
Abstract
This paper researches an AUV (Autonomous Underwater Vehicle) positioning method based on SINS (Strapdown Inertial Navigation System)/LBL (Long Base Line) tightly coupled algorithm. This algorithm mainly includes SINS-assisted searching method of optimum slant-range of underwater acoustic propagation multipath, SINS/LBL tightly coupled model and
[...] Read more.
This paper researches an AUV (Autonomous Underwater Vehicle) positioning method based on SINS (Strapdown Inertial Navigation System)/LBL (Long Base Line) tightly coupled algorithm. This algorithm mainly includes SINS-assisted searching method of optimum slant-range of underwater acoustic propagation multipath, SINS/LBL tightly coupled model and multi-sensor information fusion algorithm. Fuzzy correlation peak problem of underwater LBL acoustic propagation multipath could be solved based on SINS positional information, thus improving LBL positional accuracy. Moreover, introduction of SINS-centered LBL locating information could compensate accumulative AUV position error effectively and regularly. Compared to loosely coupled algorithm, this tightly coupled algorithm can still provide accurate location information when there are fewer than four available hydrophones (or within the signal receiving range). Therefore, effective positional calibration area of tightly coupled system based on LBL array is wider and has higher reliability and fault tolerance than loosely coupled. It is more applicable to AUV positioning based on SINS/LBL. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Protocol to Exploit Waiting Resources for UASNs
Sensors 2016, 16(3), 343; doi:10.3390/s16030343
Received: 15 December 2015 / Revised: 28 February 2016 / Accepted: 1 March 2016 / Published: 8 March 2016
Cited by 1 | PDF Full-text (2897 KB) | HTML Full-text | XML Full-text
Abstract
The transmission speed of acoustic waves in water is much slower than that of radio waves in terrestrial wireless sensor networks. Thus, the propagation delay in underwater acoustic sensor networks (UASN) is much greater. Longer propagation delay leads to complicated communication and collision
[...] Read more.
The transmission speed of acoustic waves in water is much slower than that of radio waves in terrestrial wireless sensor networks. Thus, the propagation delay in underwater acoustic sensor networks (UASN) is much greater. Longer propagation delay leads to complicated communication and collision problems. To solve collision problems, some studies have proposed waiting mechanisms; however, long waiting mechanisms result in low bandwidth utilization. To improve throughput, this study proposes a slotted medium access control protocol to enhance bandwidth utilization in UASNs. The proposed mechanism increases communication by exploiting temporal and spatial resources that are typically idle in order to protect communication against interference. By reducing wait time, network performance and energy consumption can be improved. A performance evaluation demonstrates that when the data packets are large or sensor deployment is dense, the energy consumption of proposed protocol is less than that of existing protocols as well as the throughput is higher than that of existing protocols. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle A Novel Cooperative Opportunistic Routing Scheme for Underwater Sensor Networks
Sensors 2016, 16(3), 297; doi:10.3390/s16030297
Received: 15 December 2015 / Revised: 1 February 2016 / Accepted: 22 February 2016 / Published: 26 February 2016
Cited by 12 | PDF Full-text (781 KB) | HTML Full-text | XML Full-text
Abstract
Increasing attention has recently been devoted to underwater sensor networks (UWSNs) because of their capabilities in the ocean monitoring and resource discovery. UWSNs are faced with different challenges, the most notable of which is perhaps how to efficiently deliver packets taking into account
[...] Read more.
Increasing attention has recently been devoted to underwater sensor networks (UWSNs) because of their capabilities in the ocean monitoring and resource discovery. UWSNs are faced with different challenges, the most notable of which is perhaps how to efficiently deliver packets taking into account all of the constraints of the available acoustic communication channel. The opportunistic routing provides a reliable solution with the aid of intermediate nodes’ collaboration to relay a packet toward the destination. In this paper, we propose a new routing protocol, called opportunistic void avoidance routing (OVAR), to address the void problem and also the energy-reliability trade-off in the forwarding set selection. OVAR takes advantage of distributed beaconing, constructs the adjacency graph at each hop and selects a forwarding set that holds the best trade-off between reliability and energy efficiency. The unique features of OVAR in selecting the candidate nodes in the vicinity of each other leads to the resolution of the hidden node problem. OVAR is also able to select the forwarding set in any direction from the sender, which increases its flexibility to bypass any kind of void area with the minimum deviation from the optimal path. The results of our extensive simulation study show that OVAR outperforms other protocols in terms of the packet delivery ratio, energy consumption, end-to-end delay, hop count and traversed distance. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
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Open AccessArticle Measurement and Modeling of Narrowband Channels for Ultrasonic Underwater Communications
Sensors 2016, 16(2), 256; doi:10.3390/s16020256
Received: 10 December 2015 / Revised: 15 February 2016 / Accepted: 16 February 2016 / Published: 19 February 2016
Cited by 3 | PDF Full-text (927 KB) | HTML Full-text | XML Full-text
Abstract
Underwater acoustic sensor networks are a promising technology that allow real-time data collection in seas and oceans for a wide variety of applications. Smaller size and weight sensors can be achieved with working frequencies shifted from audio to the ultrasonic band. At these
[...] Read more.
Underwater acoustic sensor networks are a promising technology that allow real-time data collection in seas and oceans for a wide variety of applications. Smaller size and weight sensors can be achieved with working frequencies shifted from audio to the ultrasonic band. At these frequencies, the fading phenomena has a significant presence in the channel behavior, and the design of a reliable communication link between the network sensors will require a precise characterization of it. Fading in underwater channels has been previously measured and modeled in the audio band. However, there have been few attempts to study it at ultrasonic frequencies. In this paper, a campaign of measurements of ultrasonic underwater acoustic channels in Mediterranean shallow waters conducted by the authors is presented. These measurements are used to determine the parameters of the so-called κ-μ shadowed distribution, a fading model with a direct connection to the underlying physical mechanisms. The model is then used to evaluate the capacity of the measured channels with a closed-form expression. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
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Open AccessArticle A Collaborative Secure Localization Algorithm Based on Trust Model in Underwater Wireless Sensor Networks
Sensors 2016, 16(2), 229; doi:10.3390/s16020229
Received: 14 December 2015 / Revised: 25 January 2016 / Accepted: 5 February 2016 / Published: 16 February 2016
Cited by 7 | PDF Full-text (7293 KB) | HTML Full-text | XML Full-text
Abstract
Localization is one of the hottest research topics in Underwater Wireless Sensor Networks (UWSNs), since many important applications of UWSNs, e.g., event sensing, target tracking and monitoring, require location information of sensor nodes. Nowadays, a large number of localization algorithms have been proposed
[...] Read more.
Localization is one of the hottest research topics in Underwater Wireless Sensor Networks (UWSNs), since many important applications of UWSNs, e.g., event sensing, target tracking and monitoring, require location information of sensor nodes. Nowadays, a large number of localization algorithms have been proposed for UWSNs. How to improve location accuracy are well studied. However, few of them take location reliability or security into consideration. In this paper, we propose a Collaborative Secure Localization algorithm based on Trust model (CSLT) for UWSNs to ensure location security. Based on the trust model, the secure localization process can be divided into the following five sub-processes: trust evaluation of anchor nodes, initial localization of unknown nodes, trust evaluation of reference nodes, selection of reference node, and secondary localization of unknown node. Simulation results demonstrate that the proposed CSLT algorithm performs better than the compared related works in terms of location security, average localization accuracy and localization ratio. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms
Sensors 2016, 16(2), 212; doi:10.3390/s16020212
Received: 27 December 2015 / Accepted: 3 February 2016 / Published: 6 February 2016
Cited by 4 | PDF Full-text (4967 KB) | HTML Full-text | XML Full-text
Abstract
Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently
[...] Read more.
Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO) is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object’s mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks
Sensors 2016, 16(1), 98; doi:10.3390/s16010098
Received: 21 November 2015 / Revised: 6 January 2016 / Accepted: 7 January 2016 / Published: 14 January 2016
Cited by 7 | PDF Full-text (4842 KB) | HTML Full-text | XML Full-text
Abstract
Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the
[...] Read more.
Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle A New Node Deployment and Location Dispatch Algorithm for Underwater Sensor Networks
Sensors 2016, 16(1), 82; doi:10.3390/s16010082
Received: 9 October 2015 / Revised: 30 December 2015 / Accepted: 6 January 2016 / Published: 9 January 2016
Cited by 6 | PDF Full-text (1854 KB) | HTML Full-text | XML Full-text
Abstract
Considering that deployment strategies for underwater sensor networks should contribute to fully connecting the networks, a Guaranteed Full Connectivity Node Deployment (GFCND) algorithm is proposed in this study. The GFCND algorithm attempts to deploy the coverage nodes according to the greedy iterative strategy,
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Considering that deployment strategies for underwater sensor networks should contribute to fully connecting the networks, a Guaranteed Full Connectivity Node Deployment (GFCND) algorithm is proposed in this study. The GFCND algorithm attempts to deploy the coverage nodes according to the greedy iterative strategy, after which the connectivity nodes are used to improve network connectivity and fully connect the whole network. Furthermore, a Location Dispatch Based on Command Nodes (LDBCN) algorithm is proposed, which accomplishes the location adjustment of the common nodes with the help of the SINK node and the command nodes. The command nodes then dispatch the common nodes. Simulation results show that the GFCND algorithm achieves a comparatively large coverage percentage and a fully connected network; furthermore, the LDBCN algorithm helps the common nodes preserve more total energy when they reach their destination locations. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL
Sensors 2016, 16(1), 42; doi:10.3390/s16010042
Received: 27 October 2015 / Revised: 22 December 2015 / Accepted: 23 December 2015 / Published: 30 December 2015
Cited by 7 | PDF Full-text (5307 KB) | HTML Full-text | XML Full-text
Abstract
This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a
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This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Mission Planning and Decision Support for Underwater Glider Networks: A Sampling on-Demand Approach
Sensors 2016, 16(1), 28; doi:10.3390/s16010028
Received: 9 November 2015 / Revised: 18 December 2015 / Accepted: 21 December 2015 / Published: 26 December 2015
Cited by 1 | PDF Full-text (1361 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes an optimal sampling approach to support glider fleet operators and marine scientists during the complex task of planning the missions of fleets of underwater gliders. Optimal sampling, which has gained considerable attention in the last decade, consists in planning the
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This paper describes an optimal sampling approach to support glider fleet operators and marine scientists during the complex task of planning the missions of fleets of underwater gliders. Optimal sampling, which has gained considerable attention in the last decade, consists in planning the paths of gliders to minimize a specific criterion pertinent to the phenomenon under investigation. Different criteria (e.g., A, G, or E optimality), used in geosciences to obtain an optimum design, lead to different sampling strategies. In particular, the A criterion produces paths for the gliders that minimize the overall level of uncertainty over the area of interest. However, there are commonly operative situations in which the marine scientists may prefer not to minimize the overall uncertainty of a certain area, but instead they may be interested in achieving an acceptable uncertainty sufficient for the scientific or operational needs of the mission. We propose and discuss here an approach named sampling on-demand that explicitly addresses this need. In our approach the user provides an objective map, setting both the amount and the geographic distribution of the uncertainty to be achieved after assimilating the information gathered by the fleet. A novel optimality criterion, called A η , is proposed and the resulting minimization problem is solved by using a Simulated Annealing based optimizer that takes into account the constraints imposed by the glider navigation features, the desired geometry of the paths and the problems of reachability caused by ocean currents. This planning strategy has been implemented in a Matlab toolbox called SoDDS (Sampling on-Demand and Decision Support). The tool is able to automatically download the ocean fields data from MyOcean repository and also provides graphical user interfaces to ease the input process of mission parameters and targets. The results obtained by running SoDDS on three different scenarios are provided and show that SoDDS, which is currently used at NATO STO Centre for Maritime Research and Experimentation (CMRE), can represent a step forward towards a systematic mission planning of glider fleets, dramatically reducing the efforts of glider operators. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
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Open AccessArticle Subjective Quality Assessment of Underwater Video for Scientific Applications
Sensors 2015, 15(12), 31723-31737; doi:10.3390/s151229882
Received: 12 November 2015 / Revised: 7 December 2015 / Accepted: 11 December 2015 / Published: 15 December 2015
Cited by 3 | PDF Full-text (2421 KB) | HTML Full-text | XML Full-text
Abstract
Underwater video services could be a key application in the better scientific knowledge of the vast oceanic resources in our planet. However, limitations in the capacity of current available technology for underwater networks (UWSNs) raise the question of the feasibility of these services.
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Underwater video services could be a key application in the better scientific knowledge of the vast oceanic resources in our planet. However, limitations in the capacity of current available technology for underwater networks (UWSNs) raise the question of the feasibility of these services. When transmitting video, the main constraints are the limited bandwidth and the high propagation delays. At the same time the service performance depends on the needs of the target group. This paper considers the problems of estimations for the Mean Opinion Score (a standard quality measure) in UWSNs based on objective methods and addresses the topic of quality assessment in potential underwater video services from a subjective point of view. The experimental design and the results of a test planned according standardized psychometric methods are presented. The subjects used in the quality assessment test were ocean scientists. Video sequences were recorded in actual exploration expeditions and were processed to simulate conditions similar to those that might be found in UWSNs. Our experimental results show how videos are considered to be useful for scientific purposes even in very low bitrate conditions. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Node Non-Uniform Deployment Based on Clustering Algorithm for Underwater Sensor Networks
Sensors 2015, 15(12), 29997-30010; doi:10.3390/s151229786
Received: 7 October 2015 / Revised: 24 November 2015 / Accepted: 26 November 2015 / Published: 1 December 2015
Cited by 11 | PDF Full-text (1475 KB) | HTML Full-text | XML Full-text
Abstract
A node non-uniform deployment based on clustering algorithm for underwater sensor networks (UWSNs) is proposed in this study. This algorithm is proposed because optimizing network connectivity rate and network lifetime is difficult for the existing node non-uniform deployment algorithms under the premise of
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A node non-uniform deployment based on clustering algorithm for underwater sensor networks (UWSNs) is proposed in this study. This algorithm is proposed because optimizing network connectivity rate and network lifetime is difficult for the existing node non-uniform deployment algorithms under the premise of improving the network coverage rate for UWSNs. A high network connectivity rate is achieved by determining the heterogeneous communication ranges of nodes during node clustering. Moreover, the concept of aggregate contribution degree is defined, and the nodes with lower aggregate contribution degrees are used to substitute the dying nodes to decrease the total movement distance of nodes and prolong the network lifetime. Simulation results show that the proposed algorithm can achieve a better network coverage rate and network connectivity rate, as well as decrease the total movement distance of nodes and prolong the network lifetime. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle SSL: Signal Similarity-Based Localization for Ocean Sensor Networks
Sensors 2015, 15(11), 29702-29720; doi:10.3390/s151129702
Received: 1 October 2015 / Revised: 8 November 2015 / Accepted: 19 November 2015 / Published: 24 November 2015
Cited by 4 | PDF Full-text (5855 KB) | HTML Full-text | XML Full-text
Abstract
Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes’ positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches
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Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes’ positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes’ positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes’ relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle EFPC: An Environmentally Friendly Power Control Scheme for Underwater Sensor Networks
Sensors 2015, 15(11), 29107-29128; doi:10.3390/s151129107
Received: 4 August 2015 / Revised: 3 November 2015 / Accepted: 11 November 2015 / Published: 17 November 2015
PDF Full-text (2246 KB) | HTML Full-text | XML Full-text
Abstract
In oceans, the limited acoustic spectrum resource is heavily shared by marine mammals and manmade systems including underwater sensor networks. In order to limit the negative impact of acoustic signal on marine mammals, we propose an environmentally friendly power control (EFPC) scheme for
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In oceans, the limited acoustic spectrum resource is heavily shared by marine mammals and manmade systems including underwater sensor networks. In order to limit the negative impact of acoustic signal on marine mammals, we propose an environmentally friendly power control (EFPC) scheme for underwater sensor networks. EFPC allocates transmission power of sensor nodes with a consideration of the existence of marine mammals. By applying a Nash Equilibrium based utility function with a set of limitations to optimize transmission power, the proposed power control algorithm can conduct parallel transmissions to improve the network’s goodput, while avoiding interference with marine mammals. Additionally, to localize marine mammals, which is a prerequisite of EFPC, we propose a novel passive hyperboloid localization algorithm (PHLA). PHLA passively localize marine mammals with the help of the acoustic characteristic of these targets. Simulation results show that PHLA can localize most of the target with a relatively small localization error and EFPC can achieve a close goodput performance compared with an existing power control algorithm while avoiding interfering with marine mammals. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)

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