Ocean Sensor Networks Research Articles

Underwater Wavelength Attack on Discrete Modulated Continuous-Variable Quantum Key Distribution.

The wavelength attack utilizes the dependence of beam splitters (BSs) on wavelength to cause legitimate users Alice and Bob to underestimate their excess noise so that Eve can steal more secret keys without being detected. Recently, the wavelength attack on Gaussian-modulated continuous-variable quantum key distribution (CV-QKD) has been researched in both fiber and atmospheric channels. However, the wavelength attack may also pose a threat to the case of ocean turbulent channels, which are vital for the secure communication of both ocean sensor networks and submarines. In this work, we propose two wavelength attack schemes on underwater discrete modulated (DM) CV-QKD protocol, which is effective for the case with and without local oscillator (LO) intensity monitor, respectively. In terms of the transmittance properties of the fused biconical taper (FBT) BS, two sets of wavelengths are determined for Eve's pulse manipulation, which are all located in the so-called blue-green band. The derived successful criterion shows that both attack schemes can control the estimated excess noise of Alice and Bob close to zero by selecting the corresponding condition parameters based on channel transmittance. Additionally, our numerical analysis shows that Eve can steal more bits when the wavelength attack controls the value of the estimated excess noise closer to zero.

A Cooperative Fault-Tolerant Mission Planner System for Unmanned Surface Vehicles in Ocean Sensor Network Monitoring and Inspection

This article presents a cooperative fault-tolerant mission planner system for a team of unmanned surface vehicles (USVs) employed for monitoring and inspection of ocean sensor networks. The problem of monitoring and inspection of ocean sensor networks is summarized as verifying the healthiness of the buoy sensors via USVs in a pre-determined zone and within a pre-defined mission time. A realistic map of the SOFAR's global Spotter network, including Spotter buoys used for observation, forecast, and hindcast of ocean and weather data is used. The mission planner system is then developed to provide a cooperative inspection of the Spotter buoys to the maximum possible numbers in an assigned mission time while the uncertainty with failure of USVs due to internal /external faults is incorporated. Extensive simulation studies together with statistical analysis are conducted to verify the performance of the proposed cooperative fault-tolerant mission planner system. The simulation results confirm the fidelity, effectiveness, and robustness of the proposed system to be implemented onboard USVs’ host computers for different monitoring and inspection missions.

Underwater Self‐Powered All‐Optical Wireless Ultrasonic Sensing, Positioning and Communication with Ultrafast Response Time and Ultrahigh Sensitivity

AbstractThe utilization of ultrasonic waves in the ocean has become an attractive topic for its applications in underwater sensor networks via a variety of research methods, such as sensing, positioning, and communication. However, it is still challenging to develop a cost‐effective, stable, fast, and accurate wireless underwater ultrasonic device with self‐power‐ability in various circumstances. Herein, a novel underwater self‐powered all‐optical wireless ultrasonic sensor (SAWS) based on triboelectrification‐induced electroluminescence (TIEL) has been proposed, in which efficient and stable TIEL can be generated under the excitation of ultrasonic waves. The SAWS has been demonstrated to accurately determine the location of the ultrasonic source with an error of less than 4.6%, and as a promising candidate for real‐time optical signal communication with an ultrafast response time of below 50 ms and an ultrahigh signal‐to‐noise ratio (SNR) of 26.02 dB. To date, the paradigm‐shift strategy for underwater ultrasonic sensing has been developed for the first time to be fully self‐powered without any wire connections. The SAWS proposed here paves a new path to the realization of a self‐powered underwater all‐optical wireless sensing system that can be effectively applied in underwater environmental monitoring, underwater robots, ocean sensor networks, etc.

Reinforcement learning-based dynamic position control of mobile node for ocean sensor networks

In this paper, a novel dynamic position control (PC) approach for mobile nodes (MNs) is proposed for ocean sensor networks (OSNs) which directly utilizes a neural network to represent a PC strategy. The calculation of position estimation no longer needs to be carried out in the proposed scheme, so the localization error is eliminated. In addition, reinforcement learning is used to train the PC strategy, so that the MN can learn a more highly accurate and fast response control strategy. Moreover, to verify its applicability to the real-world environment, we conducted field experiment deployment in OSNs consisting of a MN designed by us and some fixed nodes. The experimental results demonstrate the effectiveness of our proposed control scheme with impressive improvements on PC accuracy by more than 53% and response speed by more than 15%.

Two-Phase Robust Target Localization in Ocean Sensor Networks Using Received Signal Strength Measurements.

Target localization plays a vital role in ocean sensor networks (OSNs), in which accurate position information is not only a critical need of ocean observation but a necessary condition for the implementation of ocean engineering. Compared with other range-based localization technologies in OSNs, the received signal strength (RSS)-based localization technique has attracted widespread attention due to its low cost and synchronization-free nature. However, maintaining relatively good accuracy in an environment as dynamic and complex as the ocean remains challenging. One of the most damaging factors that degrade the localization accuracy is the uncertainty in transmission power. Besides the equipment loss, the uncertain factors in the fickle ocean environment may result in a significant deviation between the standard rated transmission power and the usable transmission power. The difference between the rated and actual transmission power would lead to an extra error when it comes to the localization in OSNs. In this case, a method that can locate the target without needing prior knowledge of the transmission power is proposed. The method relies on a two-phase procedure in which the location information and the transmission power are jointly estimated. First, the original nonconvex localization problem is transformed into an alternating non-negativity-constrained least square framework with the unknown transmission power (UT-ANLS). Under this framework, a two-stage optimization method based on interior point method (IPM) and majorization-minimization tactic (MMT) is proposed to search for the optimal solution. In the first stage, the barrier function method is used to limit the optimization scope to find an approximate solution to the problem. However, it is infeasible to approach the constraint boundary due to its intrinsic error. Then, in the second stage, the original objective is converted into a surrogate function consisting of a convex quadratic and concave term. The solution obtained by IPM is considered the initial guess of MMT to jointly estimate both the location and transmission power in the iteration. In addition, in order to evaluate the performance of IPM-MM, the Cramer Rao lower bound (CRLB) is derived. Numerical simulation results demonstrate that IPM-MM achieves better performance than the others in different scenarios.

Multi-Node Data Security Detection Method for Stratified Heterogeneous Ocean Sensor Networks

Sun, M. and Niu, R.B., 2020. Multi-node data security detection method for stratified heterogeneous ocean sensor networks. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 238-240. Coconut Creek (Florida), ISSN 0749-0208.Facing the further development of ocean detection sensor technology and the urgent situation of accelerating the expansion of my country's maritime power in the current international situation, we must conduct urgent research on the research progress and practical new development of ocean detection sensor technology. This article focuses on marine detection sensors and their development and application in the marine field. It briefly introduces the composition and system of ocean detection sensors, lists the main product types and key technologies of ocean detection sensors, introduces its main application fields according to the development of ocean detection sensors, and prospects the future development of the ocean. Detection sensor.

Cellular Communications in Ocean Waves for Maritime Internet of Things

The rapid advancement of Internet of Things (IoT) and fifth generation and beyond technologies is transforming the marine industry and research. Our understanding of the vast sea that covers 71% of the Earth’s surface is being enhanced by the various ocean sensor networks equipped with effective communication technologies. In this article, we begin with a review of the research and development status-quo of Maritime IoT (MIoT) enabled by multiple wireless communication technologies. Then, we study the impact of sea waves on radio propagation and the communications link quality. Due to the severe attenuation of sea water to radio-frequency electromagnetic wave propagation, large ocean waves can easily block the communication link between a buoy sensor and a cell tower near shore. This article for the first time uses the ocean wave modeling of coastal and oceanic waters to examine the condition of line-of-sight communications. Real wave measurement data parameters are applied in the numerical evaluation of the developed model. Finally, the critical antenna design taking into account the wave impact is numerically studied with implementation solutions proposed, and the system hardware and protocol aspects are discussed.

A Robust, Non-Cooperative Localization Algorithm in the Presence of Outlier Measurements in Ocean Sensor Networks.

As an important means of multidimensional observation on the sea, ocean sensor networks (OSNs) could meet the needs of comprehensive information observations in large-scale and multifactor marine environments. In what concerns OSNs, accurate location information is the basis of the data sets. However, because of the multipath effect—signal shadowing by waves and unintentional or malicious attacks—outlier measurements occur frequently and inevitably, which directly degrades the localization accuracy. Therefore, increasing localization accuracy in the presence of outlier measurements is a critical issue that needs to be urgently tackled in OSNs. In this case, this paper proposed a robust, non-cooperative localization algorithm (RNLA) using received signal strength indication (RSSI) in the presence of outlier measurements in OSNs. We firstly formulated the localization problem using a log-normal shadowing model integrated with a first order Taylor series. Nevertheless, the problem was infeasible to solve, especially in the presence of outlier measurements. Hence, we then converted the localization problem into the optimization problem using squared range and weighted least square (WLS), albeit in a nonconvex form. For the sake of an accurate solution, the problem was then transformed into a generalized trust region subproblem (GTRS) combined with robust functions. Although GTRS was still a nonconvex framework, the solution could be acquired by a bisection approach. To ensure global convergence, a block prox-linear (BPL) method was incorporated with the bisection approach. In addition, we conducted the Cramer–Rao low bound (CRLB) to evaluate RNLA. Simulations were carried out over variable parameters. Numerical results showed that RNLA outperformed the other algorithms under outlier measurements, notwithstanding that the time for RNLA computation was a little bit more than others in some conditions.

Reconstruction Model of Ocean Observing Complex Virtual Instrument

With the newly proposed Global Ocean Observing Integration, ocean observing scope has been expanded from the region to the global, therefore the need of large-scale ocean observing system integration has become more and more urgent. Currently, ocean observing systems enabled ocean sensor networks are commonly developed by different organizations using specific technologies and platforms, which brings several challenges in ocean observing instrument (OOI) access and ocean observing system seamless integration. Furthermore, the development of ocean observing systems often suffers from low efficiency due to the complex programming and debugging process. To solve these problems, a novel model, Complex Virtual Instrument (CVI) Model, is proposed. The model provides formal definitions on observing instrument description file, CVI description file, model calculation method, development model and interaction standard. In addition, this model establishes mathematical expressions of two model calculation operations, meanwhile builds the mapping relationship between observing instrument description file and CVI description file. The CVI based on the new model can achieve automatic access to different OOIs, seamless integration and communication for heterogeneous environments, and further implement standardized data access and management for the global unified ocean observing network. Throughout the development, integration and application of such CVI, the rationality and feasibility of the model have been evaluated. The results confirm that the proposed model can effectively implement heterogeneous system integration, improve development efficiency, make full usage of reusable components, reduce development cost, and enhance overall software system quality. We believe that our new model has great significance to promote the large-scale ocean observing system integration.

Complex Virtual Instrument Model for Ocean Sensor Networks

Virtual instrument (VI) technology is widely used, because it is more cost effective to perform data processing with computer software than with an additional hardware. Traditional VI developments often suffer from low efficiency due to the complex programming and poor interoperability. In this paper, we analyze the data management and analysis requirements of the ocean sensor networks (OSNs), identify the common characteristics of different systems, and propose complex VI model for OSNs (CVI-OSNs). It consists of an object description model to interpret the observation data, a VI model to enable comprehensive analysis of observation data, and a parameter mapping model to associate observed variables and VIs. The presented design method of CVI-OSN systems improves the development efficiency significantly and enables system interoperability. On this basis, a CVI-OSN composition model is proposed to facilitate data integration among different systems for large-scale research of ocean environment variation. The proposed model has been fully applied in the IEEE standard 2402. Moreover, we have conducted practical experiments to evaluate its performance. The result shows that our proposed model is feasible and efficient.

Tsunami Simulation Method Assimilating Ocean Bottom Pressure Data Near a Tsunami Source Region

A new method was developed to reproduce the tsunami height distribution in and around the source area, at a certain time, from a large number of ocean bottom pressure sensors, without information on an earthquake source. A dense cabled observation network called S-NET, which consists of 150 ocean bottom pressure sensors, was installed recently along a wide portion of the seafloor off Kanto, Tohoku, and Hokkaido in Japan. However, in the source area, the ocean bottom pressure sensors cannot observe directly an initial ocean surface displacement. Therefore, we developed the new method. The method was tested and functioned well for a synthetic tsunami from a simple rectangular fault with an ocean bottom pressure sensor network using 10 arc-min, or 20 km, intervals. For a test case that is more realistic, ocean bottom pressure sensors with 15 arc-min intervals along the north–south direction and sensors with 30 arc-min intervals along the east–west direction were used. In the test case, the method also functioned well enough to reproduce the tsunami height field in general. These results indicated that the method could be used for tsunami early warning by estimating the tsunami height field just after a great earthquake without the need for earthquake source information.

Underwater Optical Image Processing: a Comprehensive Review

Underwater cameras are widely used to observe the sea floor. They are usually included in autonomous underwater vehicles (AUVs), unmanned underwater vehicles (UUVs), and in situ ocean sensor networks. Despite being an important sensor for monitoring underwater scenes, there exist many issues with recent underwater camera sensors. Because of light’s transportation characteristics in water and the biological activity at the sea floor, the acquired underwater images often suffer from scatters and large amounts of noise. Over the last five years, many methods have been proposed to overcome traditional underwater imaging problems. This paper aims to review the state-of-the-art techniques in underwater image processing by highlighting the contributions and challenges presented in over 40 papers. We present an overview of various underwater image-processing approaches, such as underwater image de-scattering, underwater image color restoration, and underwater image quality assessments. Finally, we summarize the future trends and challenges in designing and processing underwater imaging sensors.

Localization for Drifting Restricted Floating Ocean Sensor Networks

Deploying wireless sensor networks in the ocean poses many challenges due to the harsh conditions of the ocean and the nonnegligible node mobility. In this paper, we propose hybrid ocean sensor networks called drifting restricted floating ocean sensor networks (DR-OSNs) for long-term maritime surveillance monitoring tasks, which combines both the advantages of wireless sensor networks and underwater wireless acoustic sensor networks. We present a localization scheme termed localization for double-head maritime sensor networks (LDSN) for DR-OSNs, which leverages the unique characteristics of DR-OSNs to establish the whole localization system after the network is deployed from a plane or a ship, and it does not need the presence of designated anchor nodes deployed underwater. The whole localization process consists of three steps with algorithms self-moored node localization (SML), underwater sensor localization (USD), and floating-node localization algorithm (FLA). The first step is for the super group nodes to localize their underwater moored nodes via an SML algorithm by leveraging the free-drifting movement of their surface nodes. Once the moored nodes in the super group nodes have localized themselves, they turn into anchor nodes underwater. Thus, in the second step, with the help of these new anchor nodes, the unlocalized underwater moored nodes use the USD algorithm to localize their positions. In the last step, when the free-drifting floating nodes without a Global Positioning System (GPS) module need to know their instant position, they apply the FLA to figure out their position. We conduct extensive simulations to evaluate the scheme, with the results indicating that LDSN achieves high localization accuracy and is an effective localization scheme for DR-OSNs.

Modified Fuzzy C Means and Ensemble based Framework for Min Cost Localization and Power Constraints in Three-Dimensional Ocean Sensor Networks

Background/Objectives: In this paper, the optimization problem is considered for Minimum Cost Localization Problem (MCLP) in 3D Ocean Sensor Network (OSN). The main aim of OSN is to localize all underwater sensors or the minimum travel distance of the ship which deploys and measures the anchors using the minimum number of anchor nodes. Methods/Statistical Analysis : Minimum Cost Discrete multi-valued Particle Swarm Optimization (MCDPSO) and Hybrid Bee Linear Genetic Colony Algorithm (HBLGCA) are combined in this Hybrid Ensemble Framework Model (HEFM). Minimum travel distance of the ship which deploys and the anchors for OSNs are determined by the finalized minimum travel distance results. In Hybrid Ensemble Framework, a set of optimization algorithm using both trilateration and local sweep operations are presented to address the problem. The set of anchor node and its travelling order sequence are picked using both trilateration and local sweep operations based on a set of HEFM which is proposed by the hardness of 3D localization. Findings: Most of the existing localization algorithms only focus on checking the localizability of a network and/or distribution of nodes within a set of anchor nodes which are static in nature and measurement of distance to localize. The main aim of today’s algorithm is to determine the min cost localization problem depending on a particular method that might not provide optimal results. To overcome all the above problem hybrid ensemble framework is formalized. Because of the complexity of the distributed approach, the current localization algorithms cause overhead and latency. Cluster based architecture for range-free localization is proposed in this paper to eradicate these problems in Wireless Sensor Network. The similar nodes are grouped using Modified Fuzzy C Means (MFCM) clustering. Some parameters such as quality of a link, energy and coverage are used to select the cluster-head. Applications/Improvements: These methods give better results for certain applications such as location-based routing due to localization problem and the results have been measured in terms of the energy, power and Quality of Service (QoS). The simulation results, show that the overhead, localization error, latency are reduced in proposed HEFM framework and the localization accuracy is increased.

Development of a Simple and Innovative Wave Energy Harvester Suitable for Ocean Sensor Network Application

The article represents a new idea about an innovative, simple and cost effective marine energy harvester for powering offshore sensor nodes working as part of Ubiquitous Sensor Network (USN). Betterment of these aqua farms by including these into wireless sensor network so that they could be remote controlled from far land, is needed to make this offshore farming more popular. For this step to be done one major concern is the powering process of the sensor nodes used as the key part of sensing or monitoring purpose of the offshore projects. So our study focuses on the design and numerical study of a wave energy harvesting device for supplying uninterrupted electric power to offshore sensor nodes serving as part of ocean environment monitoring network or any marine aquaculture farm. Analysis of the environmental and device sizing factors that makes the efficiency to deviate, have been discussed here. It is a novel, floating type, double chambered wave energy converter that uses the Oscillating Water Column technology for conversion of wave power into electrical power.

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks.

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.

Development of a Plug-and-Play Monitoring System for Cabled Observatories in the East China Sea.

Seafloor observatories enable long term, continuous and multidisciplinary observations, promising major breakthroughs in marine environment research. The effort to remotely control in situ multidisciplinary equipment performing individual and cooperative tasks is both a challenge and a guarantee for the stable operations of functional observatories. With China starting to establish ocean observatory sensor networks, in this study we describe a monitoring system for cabled observatories in the East China Sea (ESOMS) that enables this effort in a plug and play way. An information oriented monitoring architecture for ESOMS was first introduced, derived from a layered control model for ocean observatory sensor network. The architecture contained three components and enabled bidirectional information flow of observation data and commands, based on which architecture components were designed to enable plug-and-play control within related model layers. A control method enabled by general junction box (GJB) and ocean sensor markup language (OSML) was thus proposed as the plug-and-play solution for implementing ESOMS. The GJB-OSML enabled control method (GOE Control Method) mainly actualized two processes, one of which was that the in situ GJB interfaced and represented every attached sensor as a Sensing Endpoint in the cabled observatory network. The other process was that the remote ESOMS utilized the same IP/Port related information modeled by OSML to create/operate a Function Node acted as agent of the in situ sensor. A case study for using ESOMS in the Xiaoqushan Seafloor Observatory was finally presented to prove its performance and applicability. Given this successful engineering trial, the ESOMS design and implementation could be applicable and beneficial for similar efforts in future construction of seafloor observatory network both at home and abroad.

Solving Minimum Cost Three-Dimensional Localization Problem in Ocean Sensor Networks

Localization is one of the most fundamental problems in wireless sensor networks (including ocean sensor networks). Current localization algorithms mainly focus on how to localize as many sensors as possible given a set of mobile or static anchor nodes and distance measurements. In this paper, we consider an optimization problem, the minimum cost three-dimensional (3D) localization problem, in an ocean sensor network, which aims to localize all underwater sensors using the minimum number of anchor nodes or the minimum travel distance of the surface vessel which deploys and measures the anchors. Given the hardness of 3D localization, we propose a set of greedy methods to pick the anchor set and its visiting sequence. Aiming at minimizing the localization errors, we also adopt a confidence-based approach for all proposed methods to deal with noisy ranging measurements (which is very common in ocean sensor networks) and possible flip ambiguity. Our simulation results demonstrate the efficiency of all proposed methods.

IDMA-Based Compressed Sensing for Ocean Monitoring Information Acquisition with Sensor Networks

The ocean monitoring sensor network is a typically energy-limited and bandwidth-limited system, and the technical bottleneck of which is the asymmetry between the demand for large-scale and high-resolution information acquisition and the limited network resources. The newly arising compressed sensing theory provides a chance for breaking through the bottleneck. In view of this and considering the potential advantages of the emerging interleave-division multiple access (IDMA) technology in underwater channels, this paper proposes an IDMA-based compressed sensing scheme in underwater sensor networks with applications to environmental monitoring information acquisition. Exploiting the sparse property of the monitored objects, only a subset of sensors is required to measure and transmit the measurements to the monitoring center for accurate information reconstruction, reducing the requirements for channel bandwidth and energy consumption significantly. Furthermore, with the aid of the semianalytical technique of IDMA, the optimal sensing probability of each sensor is determined to minimize the reconstruction error of the information map. Simulation results with real oceanic monitoring data validate the efficiency of the proposed scheme.

Three-dimensional ocean sensor networks: A survey

The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research, oceanography, ocean monitoring, offshore exploration, and defense or homeland security. Ocean sensor networks are generally formed with various ocean sensors, autonomous underwater vehicles, surface stations, and research vessels. To make ocean sensor network applications viable, efficient communication among all devices and components is crucial. Due to the unique characteristics of underwater acoustic channels and the complex deployment environment in three dimensional (3D) ocean spaces, new efficient and reliable communication and networking protocols are needed in design of ocean sensor networks. In this paper, we aim to provide an overview of the most recent advances in network design principles for 3D ocean sensor networks, with focuses on deployment, localization, topology design, and position-based routing in 3D ocean spaces.