Internet Of Underwater Things Research Articles

Current Trend in Optical Internet of Underwater Things

Our Earth is a “blue planet” that 70 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> of the surface is covered by the oceans, but most area of oceans remain largely unexplored. Besides supporting the Earth's ecosystem and moderating climate change, oceans are rich in economically relevant natural resources ready for harvesting, such as fishery, oil and gas, and mineral resources. Ocean observation and monitoring are therefore essential for environmental preservation and sea exploration. With the availability of advanced communication techniques, researchers began to look into distributed data acquisition and ocean interconnectivity, which engendered the concepts of intelligent ocean and the Internet-of-Underwater-Things (IoUT) framework. The framework is gaining traction since one could incorporate fiber sensing, acoustic, radio frequency, and optical wireless communication technologies to establish stable, broad-coverage, and massive ocean networks. The development of underwater internet beyond acoustic communication is still in its relative infancy, and therefore more aggregated research efforts from the related communities will be required to eventually achieve breakthroughs in comprehensive IoUT technologies. This review sheds light on the practical considerations and solutions to the challenges and robustness of the optical IoUT network in terms of channel characterization, turbulence studies, mobility, receiver optimization, and the application layer.

Energy-Efficient UAV-Aided Ocean Monitoring Networks: Joint Resource Allocation and Trajectory Design

The Internet of Underwater Things (IoUT) plays a key role in maritime monitoring systems, but energy-efficient data-uploading has been a challenging task owing to energy-constrained and expensive facilities, such as buoys and underwater sensors. In this article, we present an energy-efficient data collection scheme for unmanned aerial vehicle (UAV)-aided ocean monitoring networks (OMNs), where underwater acoustic and aerial radio frequency (RF) links are considered collaboratively. Our goal is to maximize energy efficiency (EE) of the entire OMN by jointly optimizing the transmit power of buoys and sensors, scheduling their transmissions, as well as designing the UAV's trajectory; the objective function is constrained by minimum throughput thresholds, power consumption budgets, and the UAV's kinematic conditions. Furthermore, we introduce a tradeoff between the energy consumption of buoys and sensors to bridge the gap between acoustic and RF links. The formulated problem is decomposed into three subproblems and they are solved alternatively. In each iteration, we leverage Dinkelbach's method and successive convex approximation (SCA) technique to tackle the fractional program (FP) and transform an original subproblem into a convex form, respectively. Extensive simulations confirm the convergence of our proposed scheme, reveal the influence of the tradeoff on EE, and show that our scheme outweighs other benchmarks in different scenarios.

Comprehensive Ocean Information-Enabled AUV Path Planning Via Reinforcement Learning

The path planning of the autonomous underwater vehicle (AUV) has shown great potential in various Internet of Underwater Things (IoUT) applications. Although considerable efforts had been made, prior studies are confronted with some limitations. For one thing, existing work only uses the ocean current simulation model without introducing real ocean information, having not been supported by real data. For another, traditional path planning algorithms have strong environment dependence and lack flexibility: once the environment changes, they need to be remodeled and replanned. To overcome these challenges, this article proposes comprehensive ocean information D3QN (COID), an AUV path planning scheme exploiting comprehensive ocean information and reinforcement learning (RL), which consists of three steps. First, we introduce the comprehensive real ocean data, including weather, temperature, thermohaline, current, etc., and apply them into the regional ocean modeling system to generated reliable ocean current. Next, through well-designed state transition function and reward function, we build a 3-D grid model of ocean environment for RL. Furthermore, based on the framework of the double dueling deep <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> network (D3QN), COID integrates local ocean current and position features to provide state input and uses priority sampling to accelerate network convergence. The performance of COID has been evaluated and proved by numerical results, which demonstrate efficient path planning and high flexibility for expansion into different ocean environments.

ProStream: Programmable Underwater IoT Network for Multimedia Streaming

Underwater Internet of Things (IoT) faces challenges, such as low data rate, high node mobility, high error probability, and propagation delay. Furthermore, underwater multimedia communication is more challenging, as it requires a high data rate and reliable delivery. The next-generation networking paradigm—software-defined network (SDN)—improves flexibility and virtualization through programmability. SDN increases resource utilization, simplifies management, and reduces operating costs. This article proposes ProStream, a reconfigurable SDN-based underwater multihop network for improved topology management, association control, and multimedia transmission. The proposed scheme considers a network with multiple access points (APs) and mobile relays and stations. The SDN controller places flow rules in the relays, and APs are placed as per the location of the nodes. Moreover, we present a programmable station for reducing Tx/Rx complexity in underwater networks. The stations or relays are triggered through programmability to notify their sleep time and current relays and AP for association and data transmission. We evaluate the proposed scheme first through simulation-based experimentation. We also develop a small-scale real testbed prototype of the proposed SDN. The performance results show significant improvement of performance in terms of latency, throughput, and packet delivery ratio.

A Multi-Layered Energy Efficient Approach for Performance Aware Internet of Ocean Things

Over seventy-one percent of the Earth's surface is covered by oceans, a vast body of water that is sometimes divided up into smaller bodies of water called seas. Research in this area is focusing on the significant advantages of an undersea or ocean-based environment, which is impacted by the ocean's temperature. Freshwater lakes and rivers cover less than 1% of the Earth's surface. So, ecosystems are damaged and modern technology must be developed so that climate and other elements may be regulated. The Internet of Underwater Things is cutting-edge technology in the ocean and underwater environments (IoUT). It's a network of underwater items that can be used to monitor large, undiscovered aquatic areas with a real-time Internet connection. There are several uses for IoUT, including in the military, strategic fields, climate research, and thermal pollution monitoring. With the use of the World Wide Web, Ocean of Things (OoT) devices may communicate in real-time using this technology. An IoUT is one of the most important IoT areas where a dynamic network is built and many advantages are reaped from the process. Using a multi-dimensional method for cumulative performance in the marine and undersea objects area, this research publication presents use examples for IoUT. Many significant applications and real-world domains are demonstrated to interface with crucial IoUT components. The proposed approach is making use of a multi-hop and metaheuristic-based approach for the effectiveness and overall performance of IoUT. As there are so many challenges in IoUT including frequent battery reduction and energy issues, there is a need to integrate the multi-layered approach. The presented approach is effective in terms of fewer packet losses, high throughput, and minimum energy consumption.

Average Peak Age of Information in Underwater Information Collection With Sleep-Scheduling

We investigate the peak age of information (PAoI) in underwater wireless sensor networks (UWSNs), where Internet of underwater things (IoUT) nodes transmit the latest packets to the sink node, which is in charge of adjusting the sleep-scheduling to match network demands. In order to reduce PAoI, we propose active queue management (AQM) policy of the IoUT node, beneficially compresses the packets having large waiting time. Moreover, we deduce the closed-form expressions of the average PAoI as well as the energy cost relying on probability generating function and matrix-geometric solutions. Numerical results verify that the IoUT node relying on the AQM policy has a lower PAoI and energy cost in comparison to those using non-AQM policy.

Towards a Novel Architectural Design for IoT-Based Smart Marine Aquaculture

Marine farms must employ innovative solutions and new technologies to increase productivity and supply the seafood demand sustainably. In this paper, we propose a novel four-layers architecture for smart marine farms. The proposed architecture relies on recent advancements and proposes the integration of Internet of Things (IoT) and Internet of Underwater Things (loUT), edge and cloud computing, and machine learning (ML) for efficient and reliable integration of underwater sensors, data transfer among the components in a smart aquaculture farm, and real-time data processing and inference for monitoring and control of smart marine farms. The designed architecture will tackle many fundamental challenges aimed at the autonomous, intelligent, and real-time monitoring and control of smart marine farms. For each component, the issues it tackles and the challenges and guidelines to implementing it are presented. Finally, we shed light on open challenges that still prevent innovative features in smart aquaculture.

An Efficient and Secure Identity-Based Signature System for Underwater Green Transport System

The smart ocean has aroused the interest of government, business, and academia because of the wealth of marine resources. It has been suggested to use underwater Internet of Things (IoT) frameworks to collect a variety of data from smart seas that can aid in the underwater green transport system, ecological sustainability, military intelligence gathering, and a variety of other operations. Because of the limited resources accessible to IoT devices regarding communication overhead, processing expenses, and battery capacity, security and privacy concerns in underwater green transport systems have lately been a critical source of worry. In this context, We presented a unique identity-based authentication mechanism for underwater green transport systems. Our suggested solution uses lightweight authentication mechanisms that prove secure communication between different elements of the green transport system.

Simulation-based quantitative analysis of efficient data transfer routing protocols for Internet of Underwater Things

Internet of Underwater Things (IoUTs) deals in a resource-constrained environment and has several open issues, challenges, and potential applications in both onshore and offshore fields. The distinctive features of acoustic medium and persistent node mobility have spurred the development of a routing protocol for IoUT that ensures the efficient data transfer at the surface station. The efficient data transfer metrics can be achieved either by the emergence of cluster-based or chain-based routing protocols. This paper provides a simulation-based quantitative analysis of the most recent and prominent cluster-based and chain-based routing protocols for IoUT that are intended to enable the efficient data transfer from source to destination. In this context, we use NS3 to conduct extensive simulations for the quantitative analysis of different routing protocols relating to packet delivery rate, packet drop rate, normalized energy consumption, normalized network lifetime, density of alive nodes, and density of dead nodes. In addition to quantitative analysis, we also provide the performance trade-offs, limitations, and applications for IoUT routing protocols for these two classifications. In last, we also perform quantitative analysis for these two classifications head-to-head. This work aims to provide helpful insights into selecting a suitable protocol for routing applications to meet the various specifications and requirements of IoUT for efficient data dissemination.

Blockchain-based secure data transmission for internet of underwater things

Internet of Things (IoTs) is an integrated network collection of heterogeneous objects which enable seamless integration between systems, humans, devices, and various other things, to support pervasive computing for smart systems. IoT-driven systems and sensors continuously ingest data resulting in an increased volume and velocity of information which can lead to critical concerns such as security of the data and scalability of the system. The Internet of Underwater Things (IoUTs) is a specific genre of IoTs in which data related to oceanic ecosystems is continuously sensed through underwater sensors. IoUT has emerged as an innovative paradigm to support smart oceans. However, there are several critical challenges which IoUT system designers must consider such as (1) scalability of the system to handle large volumes of oceanic data and (2) security of data that is transmitted from IoT sensors deployed underwater. Blockchain as a newly emerged technology and an enabling platform allows decentralized and secure transmission of data among a wide group of untrustworthy parties. This research aims to exploit blockchain technology to secure IoUT data transmission by exploiting Interplanetary File System (IPFS) method. Additionally, this study also addresses the system’s scalability in two aspects, (1) scalability, and (2) security. We used a case study-based approach and performed experiments to evaluate the proposed solution’s usability and efficiency in terms of query response (i.e., performance), and algorithmic execution (i.e., efficiency). The proposed solution unifies blockchain technologies to secure IoT-driven systems and provides guidelines to engineer and develop next-generation of robust and secure blockchain-aided distributed IoT systems.

Performance Analysis of Cross-Layer Design for Internet of Underwater Things

Underwater communication is a diverse and complex environment and has many problems. There are many problems in modeling and operating underwater networks. Physical and data link layer specifications for underwater networking should be taken into account in terms of quality of service metrics. In this study, we construct an underwater simulation environment as a cross-layer design consisting of physical and data link layers for the Internet of Underwater Things (IoUT) Network. The IoUT network has sensors with various priorities, a central node as a hub and a gateway as a buoy. The underwater sensors communicate with CSMA/ CA-based IEEE 802.15.6 protocol on low frequencies. For a more realistic communication channel, all the features of the acoustic channel are designed and performance analyzes are discussed. In addition, the proposed IoUT is compared with terrestrial network results in terms of bit error rate, signal-to-noise ratio, packet loss ratio, end-to-end delay, radio receiver utilization, and throughput. We claim that we have made a realistic IoUT network, especially for divers, autonomous underwater vehicles with specific sensors, or for similar purposes.

Power-Efficient Data Collection Scheme for AUV-Assisted Magnetic Induction and Acoustic Hybrid Internet of Underwater Things

Power efficiency is a big concern in the Internet of Underwater Things (IoUT). The power consumption of underwater acoustic communications is typically in the scale of watts, which may drain the battery of underwater devices quickly. Whereas, the power consumption of underwater magnetic induction (MI) wireless communications is in the scale of milliwatt. Therefore, this article devotes to combine the underwater MI and acoustic communications to form a power-efficient underwater hybrid wireless network. Specifically, we investigate the power-efficient autonomous underwater vehicle (AUV) data collection schemes in an underwater MI and acoustic hybrid sensor network. We propose an alternating anchor nodes selection and flow routing (AANSFR) AUV data collection method, which alternately optimizes the AUV path planning and network data flow routing. The simulation results show that the proposed hybrid data collection scheme can significantly prolong the lifespan of underwater sensor networks.

Internet of underwater things communication: Architecture, technologies, research challenges and future opportunities

Recently, the Internet of things (IoT) paradigm has proliferated all aspect of life. The improvements IoT has made in business and industry has raised the possibility of extending its use to underwater environments, which also impacts human life. Consequently, Internet of Underwater Things (IoUT) research is intensifying. As in IoT, to deploy a successful application in IoUT, an optimal communication network is required. However, underwater environments pose unique technical challenges for setting up such networks. The aim of these networks is to achieve optimal performance required for efficient and reliable transmission within IoUT. Communication is the lifeline of a network and involves the transmission of information along a medium or path. Thus, it is critical to understand the impact of underwater environment on IoUT communication. Overall, IoUT communication utilizes underwater and terrestrial equipment. We focus on underwater communication where the medium is water and information is transmitted as acoustic/sound signals. With respect to physical, Medium Access Control (MAC) and network layers, we investigate issues associated with designing optimal IoUT networks. The underwater ecosystem varies spatially with time so, knowledge of prevailing underwater regional profiles at any time is essential. Profiles enable the construction of necessary constraints that affect optimized performance of IoUT networks. We analyze the constraints imposed by different regional profiles of underwater ecosystem and their impact on optimal IoUT communication. These constraints affect performance goals required for successful IoUT network deployment. The analysis is useful for developing state-of-the-art IoUT communication strategies based on stochastic optimization models.

Energy hole mitigation through optimized cluster head selection and strategic routing in Internet of Underwater Things

SummaryInternet of Underwater Things (IoUT) comprises various resource‐constrained sensor nodes; therefore, the routing followed in acoustic medium underwater should be energy efficient to preserve their energies. Due to large area covered in the scenarios of underwater, the multi‐hop communication leads to energy hole problem. Therefore, Energy hole mitigation through Optimized Cluster Head (CH) selection and Strategic Routing (EOCSR) in IoUT is proposed in this paper. The proposed work not only optimizes CH selection using Tunicate Swarm Algorithm but also incorporates strategic routing to address energy hole problem. The simulation results show that EOCSR improves stability and lifetime of network by 16.8% and 17.7%, as compared with recently proposed Moth Flame Optimization‐based routing method.

An integrated acoustic/LoRa system for transmission of multimedia sensor data over an Internet of Underwater Things

In the last years, underwater research has been gaining momentum due to the plethora of emerging application scenarios that are appearing, typically associated to marine wildlife protection, national borders monitoring or underwater historical sites preservation. However, research in this area is still at infancy, and implementation of the Internet of Underwater Things vision is not yet at its adulthood. One of the most critical issues is indeed associated to the need for developing a network of devices which can connect and remotely deliver data to a front-end elaboration center. To this purpose, the need for increasing network lifetime and improving the quality of the monitored parameters, while guaranteeing real time control of the network, calls for the design of tools for remotisation, actuation and control. In this paper we report about the design and development of an integrated acoustic/LoRa system for transmission of multimedia sensor data over the Internet of Underwater Things. We detail the blocks composing the system and show results obtained through field tests that assess the possibility to transmit multimedia data, as well as control data, for real time reconfiguration of the system parameters through properly designed Android or Web applications.

UDARMF: An Underwater Distributed and Adaptive Resource Management Framework

Providing qualified and sustainable communications is one of the key challenges for the Internet of Underwater Things (IoUTs) facing constrained energy supplements, non-stationary environments, and severe communication interference. Owing to spatial separation, several nodes can (and are often required to) make transmissions simultaneously to maximize network capacity. However, existing transmission solutions often face the dilemma between maximizing local capacity and global concurrency. We break this dilemma via UDARMF, an underwater distributed and adaptive resource management framework, which maximizes network capacity by supporting an increased number of communications in the network. It is a distributed deep multi-agent reinforcement learning framework that uses an observation encoder and a local utility network to coordinate the collaboration among underwater nodes by adaptively tuning its transmit parameters. We designed experiments to compare UDARMF with baselines in network capacity, concurrency, and energy efficiency. Extensive experiments were conducted to find the appropriate hyperparameters to achieve the optimal network performances. We also analyze the performance of UDARMF and baselines over diverse communication and lifetime requirements, communication environment, and energy storage. Simple closed-form approximations of UDARMF are given to reveal that an energy-constrained network’s capacity increases with available energy, following a linear trend on the logarithmic scale. Experimental results demonstrate that compared with other methods, UDARMF achieves a much better trade-off between network capacity and concurrency, at which the lifetime requirements are satisfied. The proposed framework and the closed-form approximations are likely to become valuable tools in designing and analyzing IoUTs.

AUV-Aided Hybrid Data Collection Scheme Based on Value of Information for Internet of Underwater Things

The current Internet of Underwater Things (IoUT) for marine observations and emergency responses suffers from two critical issues: 1) energy efficient and 2) timely data collection. Autonomous underwater vehicles (AUVs), serving as tools for collecting and forwarding distributed data, can deal with the unbalanced power consumption in a traditional multihop underwater communication network. However, the low speed of the AUV has not been able to guarantee the timeliness of delay-sensitive data. In this article, we introduce a hybrid data collection scheme (HDCS), taking both real-time data collection and energy efficiency (EE) issues into consideration. All sensor nodes (SNs) are first clustered based on their locations in the network. We develop an analytic expression to describe the attenuation of Value of Information (VoI), involving the relationship between the importance degree and timeliness; initial VoI could be measured by historical data. The emergency can be recognized by the presented criterion, and the transmission mode of cluster heads (CHs) in the same layer is judged by CHs themselves according to VoI. The selected CHs shall transmit the urgent data via multihop routing to avoid over attenuation of VoI. The normal data are collected by AUVs visiting all remaining CHs, and the shortest trajectory is achieved by addressing a variation of the classic traveling salesman problem (TSP). Our simulation experiments show that this mechanism can effectively increase long-term VoI while significantly improving EE.

Ultra-Low-Cost and Ultra-Low-Power, Miniature Acoustic Modems Using Multipath Tolerant Spread-Spectrum Techniques

To enable long-term, large-scale, dense underwater sensor networks or Internet of Underwater Things (IoUT) this research investigates new novel waveforms and experimental prototypes for robust communications on ultra-low-cost and ultra-low-power, miniature acoustic modems. Spread-spectrum M-ary orthogonal signalling (MOS) is used with symbols constructed from subsequences of long pseudorandom codes. This decorrelates multipath signals, even when the time-spread spans many symbols, so they present as random noise. A highly cost-engineered and miniaturised prototype acoustic modem implementation was created, for the 24 kHz–32 kHz band, with low receive power consumption (12.5 mW) and transmit power of &lt;1 W. Simulations show that the modulation scheme achieves 640 bit/s at −4.5 dB with AWGN or the equivalent level of multipath energy. Experimental validation of the hardware shows successful point-to-point communication at ranges of &gt;3 km in lakes and &gt;2 km in the sea including severe multipath. In lake testing of a 7-node, multi-hop, sensor network with TDA-MAC protocol, packet delivery was near 100% for all nodes. Trials of acoustic sensor nodes in the North Sea achieved 99.5% data delivery over a 3-month period and a wide range of sea conditions. Modulation and hardware have proven reliable in a variety of underwater environments. Competitive range and throughput with low cost and power are attractive for large-scale and long-term battery-operated networks. This research has delivered a viable and affordable communication technology for future IoUT applications.

Underwater IoT Network by Blind MIMO OFDM Transceiver Based on Probabilistic Stone’s Blind Source Separation

Telecommunications systems with Multi-Input Multi-Output (MIMO) structure using Orthogonal Frequency Division Modulation (OFDM) have great potential for efficient application to a network of Internet of Things (IoT) at a high data rate. When the IoT network is among the underwater sensory devices known as the Internet of Underwater Things (IoUT), the electromagnetic wave cannot play the role of baseband signal due to rapid fall-off inside the water. Thus, acoustic OFDM is a reliable replacement for conventional OFDM inside the water. A blind structure for MIMO acoustic OFDM using Independent Component Analysis (ICA) brings even further advantages in data rate and energy consumption by avoiding the required pilot and preamble data. This research work presents a blind MIMO Acoustic OFDM blind transceiver for IoUT based on Probabilistic Stone’s Blind Source Separation (PS-BSS). The proposed technique has multiple times lower complexity compared to the ICA-based technique while maintaining a comparable efficiency. As observed in the results carried out with 100 Monte Carlo runs of transmission of random data bits over a highly sparse channel that is the common case of an underwater environment, the proposed PS-BSS-based technique dominates the ICA-based one, and as the sparseness of the channel decreases, its efficiency is comparable to the ICA-based technique. Thus, in the case of a highly sparse channel, the proposed technique is superior in both aspects of efficiency and complexity, while over lower sparseness, due to its comparative efficiency, it can be hired as an optimum technique fulfilling a fair tradeoff between efficiency and complexity.

Low Complexity Single Carrier Frequency Domain Detectors for Internet of Underwater Things (IoUT)s

This paper proposes low complexity detection for internet of underwater things communication. The signal is transmitted from the source to the destination using several sensors. To simplify the computational operations at the transmitter and the sensory nodes, a single carrier frequency domain equalizer is proposed and amplify-and-forward protocols are employed. Fast Fourier transform and use of cyclic prefix are also proposed to simplify these algorithms when compared to time-domain equalization. As precise channel data is difficult to capture in underwater communications, the adaptive implementation of FDE is proposed as a solution that can be employed when the channel experiences a fast doppler shift. The two adaptive detectors are based on the least mean-square and recursive least square principles. Numerical simulations show that the performance of the bit error rate performance of the proposed detectors is close to that of the ideal minimum mean square error.