A software-defined multi-modal wireless sensor network for ocean monitoring

Author:

Luo Hanjiang1ORCID,Wang Xu1,Xu Ziyang1,Liu Chao2ORCID,Pan Jeng-Shyang1

Affiliation:

1. Shandong University of Science and Technology, Qingdao, China

2. Ocean University of China, Qingdao, China

Abstract

The software-defined networking paradigm enables wireless sensor networks as a programmable and reconfigurable network to improve network management and efficiency. However, several challenges arise when implementing the concept of software-defined networking in maritime wireless sensor networks, as the networks operate in harsh ocean environments, and the dominant underwater acoustic systems are with limited bandwidth and high latency, which render the implementation of software-defined networking central-control difficult. To cope with the problems and meet demand for high-speed data transmission, we propose a radio frequency–acoustic software-defined networking-based multi-modal wireless sensor network which leverages benefits of both radio frequency and acoustic communication systems for ocean monitoring. We first present the software-defined networking-based multi-modal network architecture, and then explore two examples of applications with this architecture: network deployment and coverage for intrusion detection with both grid-based and random deployment scenarios, and a novel underwater testbed design by incorporating radio frequency–acoustic multi-modal techniques to facilitate marine sensor network experiments. Finally, we evaluate the performance of deployment and coverage of software-defined networking-based multi-modal wireless sensor network through simulations with several scenarios to verify the effectiveness of the network.

Funder

national natural science foundation of china

natural science foundation of shandong province

SDUST Research Fund

shandong university of science and technology

Publisher

SAGE Publications

Subject

Computer Networks and Communications,General Engineering

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Age of information minimization in UAV-assisted data harvesting networks by multi-agent deep reinforcement curriculum learning;Expert Systems with Applications;2024-12

2. MIoT: An IoT System for Dynamic Ocean Monitoring and Data Collection;2024 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET);2024-03-21

3. A Systematic Analysis, Outstanding Challenges, and Future Prospects for Routing Protocols and Machine Learning Algorithms in Underwater Wireless Acoustic Sensor Networks;Journal of Interconnection Networks;2024-02-01

4. Assessing the Performance of Autonomous and Adaptive Communications Systems in Wireless Sensor Networks;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

5. An Intelligent Adaptive Neuro-Fuzzy for Solving the Multipath Congestion in Internet of Things;Journal of Information Systems Engineering and Management;2023-12-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3