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Advances in Underwater Acoustic Communication and Ocean Sensor Networks
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Advances in Underwater Acoustic Communication and Ocean Sensor Networks

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Physical Oceanography".

Deadline for manuscript submissions: 10 October 2024 | Viewed by 2227

Special Issue Editors

Prof. Dr. Huafeng Wu

E-Mail Website
Guest Editor
Merchant Marine College, Shanghai Maritime University, Shanghai, China
Interests: marine information technology; ocean sensor networks; WSN; distributed computing; ocean big data
Prof. Dr. Dezhi Han

E-Mail Website
Guest Editor
College of Information Engineering, Shanghai Maritime University, Shanghai, China
Interests: UWSN/SWSN security; ocean big data; cloud computing security; cloud storage security

Special Issue Information

Dear Colleagues,

The vast ocean covers 140 million square miles, some 72 percent of the Earth's surface, and is one of the most valuable natural resources. Ocean exploration is an essential step for sustainable global resource development. There has been an accelerated advancement in communication technologies in recent decades. Underwater acoustic communication (UAC) and Ocean Sensor Networks (OSNs) enable us to interact with underwater information and terrestrial users, being a critical means of ocean exploration. However, a changeable and highly dynamic ocean environment deteriorates the performance of UAC and OSNs. A bottleneck for current underwater technologies is acquiring a robust and anti-interference UAC and OSN to prompt civilized or military underwater applications. To this end, the Special Issue aims to publish the most exciting research on some topics related to advanced UAC and OSN technologies, provide a rapid turn-around time for reviewing and publishing, and freely disseminate the articles for research, teaching, and reference purposes.

The topics includes but is not limited to:

  • Underwater acoustic communication (UAC);
  • Ocean Sensor Network (OSN);
  • Underwater/surface wireless sensor networks (UWSNs/SWSNs);
  • UWSN/SWSN security;
  • Ad-hoc network;
  • Channel estimation;
  • MAC and routing protocol;
  • Target localization in UWSNs/SWSNs;
  • Ocean big data;
  • UWSN/SWSN signal processing;
  • Intelligent-ship-aided UWSNs/SWSNs;
  • Artificial intelligence in UACs;
  • Autonomous underwater/surface vehicle (AUV/ASV)-aided ocean exploration;
  • Ocean observation network;
  • Polar communication and networking;
  • Marine communication and navigation;
  • Ocean data processing

Prof. Dr. Huafeng Wu
Prof. Dr. Dezhi Han
Guest Editors

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. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly 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.

Keywords

  • underwater acoustic communication (UAC)
  • Ocean Sensor Network (OSN)
  • underwater/surface wireless sensor networks (UWSNs/SWSNs)
  • UWSN/SWSN security
  • Ad-hoc network
  • channel estimation
  • MAC and routing protocol
  • target localization in UWSNs/SWSNs
  • ocean big data
  • UWSN/SWSN signal processing
  • intelligent-ship-aided UWSNs/SWSNs
  • artificial intelligence in UACs
  • autonomous underwater/surface vehicle (AUV/ASV)-aided ocean exploration
  • ocean observation network
  • polar communication and networking
  • marine communication and navigation
  • ocean data processing

Published Papers (3 papers)

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23 pages, 2335 KiB  
Article
Enhanced Target Localization in the Internet of Underwater Things through Quantum-Behaved Metaheuristic Optimization with Multi-Strategy Integration
by Xiaojun Mei, Fahui Miao, Weijun Wang, Huafeng Wu, Bing Han, Zhongdai Wu, Xinqiang Chen, Jiangfeng Xian, Yuanyuan Zhang and Yining Zang
J. Mar. Sci. Eng. 2024, 12(6), 1024; https://doi.org/10.3390/jmse12061024 - 19 Jun 2024
Viewed by 295
Abstract
Underwater localization is considered a critical technique in the Internet of Underwater Things (IoUTs). However, acquiring accurate location information is challenging due to the heterogeneous underwater environment and the hostile propagation of acoustic signals, especially when using received signal strength (RSS)-based techniques. Additionally, [...] Read more.
Underwater localization is considered a critical technique in the Internet of Underwater Things (IoUTs). However, acquiring accurate location information is challenging due to the heterogeneous underwater environment and the hostile propagation of acoustic signals, especially when using received signal strength (RSS)-based techniques. Additionally, most current solutions rely on strict mathematical expressions, which limits their effectiveness in certain scenarios. To address these challenges, this study develops a quantum-behaved meta-heuristic algorithm, called quantum enhanced Harris hawks optimization (QEHHO), to solve the localization problem without requiring strict mathematical assumptions. The algorithm builds on the original Harris hawks optimization (HHO) by integrating four strategies into various phases to avoid local minima. The initiation phase incorporates good point set theory and quantum computing to enhance the population quality, while a random nonlinear technique is introduced in the transition phase to expand the exploration region in the early stages. A correction mechanism and exploration enhancement combining the slime mold algorithm (SMA) and quasi-oppositional learning (QOL) are further developed to find an optimal solution. Furthermore, the RSS-based Cramér–Raolower bound (CRLB) is derived to evaluate the effectiveness of QEHHO. Simulation results demonstrate the superior performance of QEHHO under various conditions compared to other state-of-the-art closed-form-expression- and meta-heuristic-based solutions. Full article
(This article belongs to the Special Issue Advances in Underwater Acoustic Communication and Ocean Sensor Networks)
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21 pages, 4724 KiB  
Article
ETE-SRSP: An Enhanced Optimization of Tramp Ship Routing and Scheduling
by Xiaohu Huang, Yuhan Liu, Mei Sha, Bing Han, Dezhi Han and Han Liu
J. Mar. Sci. Eng. 2024, 12(5), 817; https://doi.org/10.3390/jmse12050817 - 14 May 2024
Viewed by 524
Abstract
In the contemporary tramp shipping industry, route optimization and scheduling are directly linked to enhancements in operations, economics, and the environment, making them key factors for the effective management of maritime transportation. To enhance effective ship-to-cargo matching and the refinement of maritime transportation [...] Read more.
In the contemporary tramp shipping industry, route optimization and scheduling are directly linked to enhancements in operations, economics, and the environment, making them key factors for the effective management of maritime transportation. To enhance effective ship-to-cargo matching and the refinement of maritime transportation itineraries, this paper introduces a time efficiency and carbon dioxide emission multi-objective optimization algorithm named ETE-SRSP (efficiency–time–emission multi-optimization algorithm). ETE-SRSP incorporates several factors, including the initial positions of ships, time windows for loading and unloading operations, and varying sailing speeds. Within the ETE-SRSP framework, pioneering an approach that integrates ballast and laden sailing velocities as decisional parameters, it employs a multi-objective optimization technique to investigate the intricate interplay between temporal efficiency and carbon dioxide emissions. Additionally, the model’s proficiency in mitigating emissions and managing costs is clearly demonstrated through the optimization of these objectives, thereby offering a robust framework for decision support. The experimental results show that the optimal sailing speeds derived from the ETE-SRSP, under typical time-weight scenarios, can achieve an optimal balance between emission reduction and cost control. In summary, this study underscores the optimization strategy’s potential to effectively address the maritime sector’s need for economic growth and ecological conservation, showcasing its practical value in the industry. Full article
(This article belongs to the Special Issue Advances in Underwater Acoustic Communication and Ocean Sensor Networks)
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15 pages, 806 KiB  
Article
Energy-Efficient Resource Optimization for IRS-Assisted VLC-Enabled Offshore Communication System
by Woping Xu and Li Gu
J. Mar. Sci. Eng. 2024, 12(5), 772; https://doi.org/10.3390/jmse12050772 - 5 May 2024
Viewed by 525
Abstract
In this paper, a downlink energy efficiency maximization problem is investigated in an intelligent reflective surface (IRS)-assisted visible light communication system. In order to extend wireless communication coverage of the onshore base station, an IRS mounted on a unmanned aerial vehicle (UAV) is [...] Read more.
In this paper, a downlink energy efficiency maximization problem is investigated in an intelligent reflective surface (IRS)-assisted visible light communication system. In order to extend wireless communication coverage of the onshore base station, an IRS mounted on a unmanned aerial vehicle (UAV) is introduced to assist an onshore lighthouse with simultaneously providing remote ship users wireless communication services and illumination. Aiming to maximizing the energy efficiency of the proposed system, a resource allocation problem is formulated as the ratio of the achievable system sum rate to the total power consumption under the constraints of the user’s data requirement and transmit power budget. Due to the non-convexity of the proposed problem, the Dinkelbach method and mean-square error (MSE) method are adopted to turn the non-convex origin problem into two equivalent problems, namely transmit beamforming and reflected phase shifting. The Lagrangian method and semidefinite relaxation technique are used to obtain the closed-form solutions of these two subproblems. Accordingly, an alternative optimization-based resource allocation scheme is proposed to obtain the optimal system energy efficiency. The simulation results show that the proposed scheme performs better in terms of energy efficiency over benchmark schemes. Full article
(This article belongs to the Special Issue Advances in Underwater Acoustic Communication and Ocean Sensor Networks)
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