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Underwater Sensor Networks for Communication, Navigation, and Localization

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

Deadline for manuscript submissions: 31 August 2024 | Viewed by 8051

Special Issue Editor

Department of Computer Engineering, Gachon University, Sujeong-gu, Seongnam 13120, Republic of Korea
Interests: robotics; Internet of Things (IoT); wireless sensor networks (WSNs); underwater communication and localization; underwater sensor networks (USNs); AI; deep learning
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Special Issue Information

Dear Colleagues,

Around 70% of the Earth is covered by water, with numerous submerged locations remaining to be monitored and supervised. Furthermore, there are numerous types of undersea environments. Advances in underwater sensors and underwater sensor networks are making these places more accessible since the sensors are less expensive, have greater computing capability, and use less battery power. Every day, the number of applications for which they can be used expands. Moreover, Autonomous underwater vehicles (AUVs) have the potential to remove humans from dangerous underwater duties such as coral planting and underwater research. Despite decades of development, most underwater robots today are still linked by cables and cannot reach full autonomy. Unmanned aerial vehicles, or AUVs in the air, have experienced tremendous research advancement and have become a popular platform for diverse sensing. More research is needed to improve AUV performance in localization, navigation, and communication. This Special Issue will collect articles on the most recent applications, developments, and problems in underwater sensor nodes and underwater sensor networks.

Authors are encouraged to submit original papers that have not been submitted to another conference or journal. The state of the art, standards, implementations, running experiments, applications, fresh research proposals, and industrial case studies can all be considered.

Topics that could be considered include, but are not limited to:

  • Underwater sensor network wireless communication;
  • Underwater sensor network communication, localization, distributed localization;
  • Three-dimensional localization, and recursive localization;
  • Underwater object detection, target tracking, gas data, and multimedia communication using autonomous underwater vehicles;
  • Identification of living creatures (plants and animals) in the sea;
  • Tracing and tracking paths of underwater submarines;
  • Databases and big data for underwater systems control;
  • Autonomous underwater vehicle localization;
  • Underwater Internet of Things (UIoT);
  • Underwater acoustic, visible light, radio frequency, and magnetic communications;
  • Underwater acoustics, machine learning, deep learning, and signal processing;
  • Underwater digital twins, virtual reality, augmented reality, and mixed reality;
  • Underwater signal and image processing, marine environment and marine sciences, saliency detection, and underwater/underground mining;
  • Machine learning/Deep learning-based sensors’ signal processing for autonomous underwater vehicles.

Dr. Inam Ullah
Guest Editor

Manuscript Submission Information

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

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.

Published Papers (6 papers)

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Research

22 pages, 3182 KiB  
Article
Underwater Multi-Channel MAC with Cognitive Acoustics for Distributed Underwater Acoustic Networks
by Changho Yun
Sensors 2024, 24(10), 3027; https://doi.org/10.3390/s24103027 - 10 May 2024
Viewed by 280
Abstract
The advancement of underwater cognitive acoustic network (UCAN) technology aims to improve spectral efficiency and ensure coexistence with the underwater ecosystem. As the demand for short-term underwater applications operated under distributed topologies, like autonomous underwater vehicle cluster operations, continues to grow, this paper [...] Read more.
The advancement of underwater cognitive acoustic network (UCAN) technology aims to improve spectral efficiency and ensure coexistence with the underwater ecosystem. As the demand for short-term underwater applications operated under distributed topologies, like autonomous underwater vehicle cluster operations, continues to grow, this paper presents Underwater Multi-channel Medium Access Control with Cognitive Acoustics (UMMAC-CA) as a suitable channel access protocol for distributed UCANs. UMMAC-CA operates on a per-frame basis, similar to the Multi-channel Medium Access Control with Cognitive Radios (MMAC-CR) designed for distributed cognitive radio networks, but with notable differences. It employs a pre-determined data transmission matrix to allow all nodes to access the channel without contention, thus reducing the channel access overhead. In addition, to mitigate the communication failures caused by randomly occurring interferers, UMMAC-CA allocates at least 50% of frame time for interferer sensing. This is possible because of the fixed data transmission scheduling, which allows other nodes to sense for interferers simultaneously while a specific node is transmitting data. Simulation results demonstrate that UMMAC-CA outperforms MMAC-CR across various metrics, including those of the sensing time rate, controlling time rate, and throughput. In addition, except for in the case where the data transmission time coefficient equals 1, the message overhead performance of UMMAC-CA is also superior to that of MMAC-CR. These results underscore the suitability of UMMAC-CA for use in challenging underwater applications requiring multi-channel cognitive communication within a distributed network architecture. Full article
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22 pages, 4327 KiB  
Article
An Underwater Source Location Privacy Protection Scheme Based on Game Theory in a Multi-Attacker Cooperation Scenario
by Beibei Wang, Xiufang Yue, Kun Hao, Yonglei Liu, Zhisheng Li and Xiaofang Zhao
Sensors 2024, 24(9), 2851; https://doi.org/10.3390/s24092851 - 30 Apr 2024
Viewed by 419
Abstract
Ensuring source location privacy is crucial for the security of underwater acoustic sensor networks amid the growing use of marine environmental monitoring. However, the traditional source location privacy scheme overlooks multi-attacker cooperation strategies and also has the problem of high communication overhead. This [...] Read more.
Ensuring source location privacy is crucial for the security of underwater acoustic sensor networks amid the growing use of marine environmental monitoring. However, the traditional source location privacy scheme overlooks multi-attacker cooperation strategies and also has the problem of high communication overhead. This paper addresses the aforementioned limitations by proposing an underwater source location privacy protection scheme based on game theory under the scenario of multiple cooperating attackers (SLP-MACGT). First, a transformation method of a virtual coordinate system is proposed to conceal the real position of nodes to a certain extent. Second, through using the relay node selection strategy, the diversity of transmission paths is increased, passive attacks by adversaries are resisted, and the privacy of source nodes is protected. Additionally, a secure data transmission technique utilizing fountain codes is employed to resist active attacks by adversaries, ensuring data integrity and enhancing data transmission stability. Finally, Nash equilibrium could be achieved after the multi-round evolutionary game theory of source node and multiple attackers adopting their respective strategies. Simulation experiments and performance evaluation verify the effectiveness and reliability of SLP-MACGT regarding aspects of the packet forwarding success rate, security time, delay and energy consumption: the packet delivery rate average increases by 30%, security time is extended by at least 85%, and the delay is reduced by at least 90% compared with SSLP, PP-LSPP, and MRGSLP. Full article
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21 pages, 5017 KiB  
Article
Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks
by Duoliang Han, Xiujuan Du, Lijuan Wang, Xiuxiu Liu and Xiaojing Tian
Sensors 2023, 23(23), 9323; https://doi.org/10.3390/s23239323 - 22 Nov 2023
Cited by 1 | Viewed by 665
Abstract
Routing protocols based on trust mechanisms have been widely investigated for wireless sensor networks, and the works have achieved good results, while there are few works on trusted routing for underwater acoustic networks (UANs). However, trust-aware routing is the key to improving the [...] Read more.
Routing protocols based on trust mechanisms have been widely investigated for wireless sensor networks, and the works have achieved good results, while there are few works on trusted routing for underwater acoustic networks (UANs). However, trust-aware routing is the key to improving the packet delivery rate and the energy efficiency of UANs. Therefore, inspired by the theory of trust evaluation, a trust-aware and fuzzy logic-based reliable layering routing protocol (TAFLRLR) is proposed. In the TAFLRLR protocol, to avoid the problem of the void area and improve the transmission reliability, the candidate nodes of the next-hop forwarding nodes are determined according to the layers of neighbor nodes. Moreover, a fuzzy logic-based trust evaluation mechanism (FLTEM) is provided, which employs the fuzzy comprehensive evaluation decision model to calculate the comprehensive trust value for underwater sensor nodes. Further, the node density of a candidate node and its comprehensive trust value are taken as the input of a fuzzy control system and the forwarding probability (FP) of the node is taken as the output, and the candidate node with the highest FP is selected as the best forwarding node. Simulation results illustrate the superiority and effectiveness of the TAFLRLR protocol in terms of energy efficiency, routing reliability, and transmission reliability. Full article
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18 pages, 12204 KiB  
Article
Multi-Domain Rapid Enhancement Networks for Underwater Images
by Longgang Zhao and Seok-Won Lee
Sensors 2023, 23(21), 8983; https://doi.org/10.3390/s23218983 - 5 Nov 2023
Viewed by 1280
Abstract
Images captured during marine engineering operations suffer from color distortion and low contrast. Underwater image enhancement helps to alleviate these problems. Many deep learning models can infer multi-source data, where images with different perspectives exist from multiple sources. To this end, we propose [...] Read more.
Images captured during marine engineering operations suffer from color distortion and low contrast. Underwater image enhancement helps to alleviate these problems. Many deep learning models can infer multi-source data, where images with different perspectives exist from multiple sources. To this end, we propose a multichannel deep convolutional neural network (MDCNN) linked to a VGG that can target multi-source (multi-domain) underwater image enhancement. The designed MDCNN feeds data from different domains into separate channels and implements parameters by linking VGGs, which improves the domain adaptation of the model. In addition, to optimize performance, multi-domain image perception loss functions, multilabel soft edge loss for specific image enhancement tasks, pixel-level loss, and external monitoring loss for edge sharpness preprocessing are proposed. These loss functions are set to effectively enhance the structural and textural similarity of underwater images. A series of qualitative and quantitative experiments demonstrate that our model is superior to the state-of-the-art Shallow UWnet in terms of UIQM, and the performance evaluation conducted on different datasets increased by 0.11 on average. Full article
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19 pages, 585 KiB  
Article
A Novel Feature-Selection Algorithm in IoT Networks for Intrusion Detection
by Anjum Nazir, Zulfiqar Memon, Touseef Sadiq, Hameedur Rahman and Inam Ullah Khan
Sensors 2023, 23(19), 8153; https://doi.org/10.3390/s23198153 - 28 Sep 2023
Cited by 3 | Viewed by 2052
Abstract
The Internet of Things (IoT) and network-enabled smart devices are crucial to the digitally interconnected society of the present day. However, the increased reliance on IoT devices increases their susceptibility to malicious activities within network traffic, posing significant challenges to cybersecurity. As a [...] Read more.
The Internet of Things (IoT) and network-enabled smart devices are crucial to the digitally interconnected society of the present day. However, the increased reliance on IoT devices increases their susceptibility to malicious activities within network traffic, posing significant challenges to cybersecurity. As a result, both system administrators and end users are negatively affected by these malevolent behaviours. Intrusion-detection systems (IDSs) are commonly deployed as a cyber attack defence mechanism to mitigate such risks. IDS plays a crucial role in identifying and preventing cyber hazards within IoT networks. However, the development of an efficient and rapid IDS system for the detection of cyber attacks remains a challenging area of research. Moreover, IDS datasets contain multiple features, so the implementation of feature selection (FS) is required to design an effective and timely IDS. The FS procedure seeks to eliminate irrelevant and redundant features from large IDS datasets, thereby improving the intrusion-detection system’s overall performance. In this paper, we propose a hybrid wrapper-based feature-selection algorithm that is based on the concepts of the Cellular Automata (CA) engine and Tabu Search (TS)-based aspiration criteria. We used a Random Forest (RF) ensemble learning classifier to evaluate the fitness of the selected features. The proposed algorithm, CAT-S, was tested on the TON_IoT dataset. The simulation results demonstrate that the proposed algorithm, CAT-S, enhances classification accuracy while simultaneously reducing the number of features and the false positive rate. Full article
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21 pages, 3592 KiB  
Article
Advancements in Neighboring-Based Energy-Efficient Routing Protocol (NBEER) for Underwater Wireless Sensor Networks
by Sayyed Mudassar Shah, Zhaoyun Sun, Khalid Zaman, Altaf Hussain, Inam Ullah, Yazeed Yasin Ghadi, Muhammad Abbas Khan and Rashid Nasimov
Sensors 2023, 23(13), 6025; https://doi.org/10.3390/s23136025 - 29 Jun 2023
Cited by 16 | Viewed by 1798
Abstract
Underwater wireless sensor networks (UWSNs) have gained prominence in wireless sensor technology, featuring resource-limited sensor nodes deployed in challenging underwater environments. To address challenges like power consumption, network lifetime, node deployment, topology, and propagation delays, cooperative transmission protocols like co-operative (Co-UWSN) and co-operative [...] Read more.
Underwater wireless sensor networks (UWSNs) have gained prominence in wireless sensor technology, featuring resource-limited sensor nodes deployed in challenging underwater environments. To address challenges like power consumption, network lifetime, node deployment, topology, and propagation delays, cooperative transmission protocols like co-operative (Co-UWSN) and co-operative energy-efficient routing (CEER) have been proposed. These protocols utilize broadcast capabilities and neighbor head node (NHN) selection for cooperative routing. This research introduces NBEER, a novel neighbor-based energy-efficient routing protocol tailored for UWSNs. NBEER aims to surpass the limitations of Co-UWSN and CEER by optimizing NHNS and cooperative mechanisms to achieve load balancing and enhance network performance. Through comprehensive MATLAB simulations, we evaluated NBEER against Co-UWSN and CEER, demonstrating its superior performance across various metrics. NBEER significantly maximizes end-to-end delay, reduces energy consumption, improves packet delivery ratio, extends network lifetime, and enhances total received packets analysis compared to the existing protocols. Full article
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