CPS: Synergy: Collaborative Research: DEUS: Distributed, Efficient, Ubiquitous and Secure Data Delivery Using Autonomous Underwater Vehicles

CPS：协同：协作研究：DEUS：使用自主水下航行器进行分布式、高效、无处不在和安全的数据传输

• 批准号: 1646607
• 负责人: Miao Pan
• 金额: $ 60万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646607&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; DEUS

Ocean Big Data (OBD) is an emerging area of research that benefits ocean environmental monitoring, offshore exploration, disaster prevention, and military surveillance. It is now affordable for oil and gas companies, fishing industry, militaries, and marine researchers to deploy physical undersea sensor systems to obtain strategic advantages. However, these sensing activities are scattered, isolated, and often follow the traditional "deploy, wait, retrieve, and post-process" routine. Since transmitting information underwater remains difficult and unreliable, these sensors lack a cyber interconnection, which severely limits ocean cyber-physical systems. This project aims to providing a viable cyber interconnection scheme that enables distributed, efficient, ubiquitous, and secure (DEUS) data delivery from underwater sensors to the surface station. The proposed cyber interconnection scheme features cheap underwater sensor nodes with energy harvesting capability, a fleet of autonomous underwater vehicles (AUVs) for information ferrying, advanced magnetic-induction (MI) antenna design using ferrite material, distributed algorithms for efficient data collection via AUVs, and secure data delivery protocols. The success of this project will help push the frontier of Internet of Things in Oceans (IoTO) and OBD, both of which will find numerous underwater applications in offshore oil spill response, fisheries management, storm preparedness, etc., which impact the economy and well-being of not only coastal regions but also inland states. The project will also provide special interdisciplinary training opportunities for both graduate and undergraduate students, particularly women and minority students, through both research work and related courses on underwater wireless communication, network security, and AUV designs.The DEUS project provides a viable cyber interconnection scheme that enables distributed, efficient, ubiquitous, and secure data delivery in underwater environment via four synergistic thrusts: (1) integration of underwater wireless sensor and communication systems, which will enhance the current MI and light communication means of underwater sensors, integrate acoustic transmission systems for long-range communications between anchor nodes and AUVs, and design energy harvesting and replenishment solutions to prolong the lifetime of underwater sensors (30+ years); (2) distributed and ubiquitous data delivery via multiple AUVs, which aims to collect the distributed data and deliver them ubiquitously throughout the underwater network by employing ferrite material and triaxial induction antennas and mounting them outside of the AUV body for MI enhancement, and developing algorithms of multiple AUVs' path-planning, trajectory optimization, etc. under dynamic network conditions; (3) efficiency and security in data delivery, which designs network algorithms to improve the efficiency and security of data delivery. Instead of collecting data from every sensor via acoustic communications, the AUVs choose some sensors to collect data with the high data rate transmission mode in near field (e.g., light), and allowing the sensor far away from the AUVs to send its data either directly to AUVs via acoustic wave or to its nearby chosen sensors via MI/light communications. A secure data delivery scheme will also be developed to not only secure the data delivery against typical malicious attacks and guarantee the integrity of collected data, but also allow the data aggregation of one business entity without knowing others' private business information; (4) experimental validation and testing, which will verify the proposed data delivery schemes, and quantitatively present the performance gains through simulations, experiments and field test, based on existing facilities.

海洋大数据（OBD）是一个新兴领域，有利于海洋环境监测，海上勘探，预防灾难和军事监视。现在，对于石油和天然气公司，捕鱼行业，军队和海洋研究人员来说，它可以负担得起，以部署实物底层传感器系统以获得战略优势。但是，这些感应活动是分散的，孤立的，并且经常遵循传统的“部署，等待，检索和后处理”常规。由于水下传输信息仍然很困难和不可靠，因此这些传感器缺乏网络互连，这严重限制了海洋网络物理系统。该项目旨在提供一个可行的网络互连方案，该方案可实现分布式，高效，无处不在和安全（DEU）的数据传输，从水下传感器到水面站。拟议的网络互连方案具有廉价的水下传感器节点，具有能源收集能力，一支自动驾驶水下车辆（AUVS），用于信息渡轮，先进的磁性感应（MI）天线设计，使用铁矿设计，使用Ferrite材料，分布式算法，分布式算法，以通过AUV和安全的数据输送协议收集有效的数据，并提供了有效的数据。该项目的成功将有助于推动海洋（Ioto）和OBD中物联网的边界，这两者都会在海上石油溢油响应，渔业管理，风暴备件等中发现许多水下应用，这不仅影响了沿海地区，而且还影响内陆州的经济和福祉。该项目还将通过研究工作以及有关水下无线沟通，网络安全和AUV设计的研究工作以及相关课程为研究生和本科生，尤其是妇女和少数群体的学生提供特殊的跨学科培训机会。DEUS项目提供了可行的网络互连方案，提供了一个可行的网络互连方案，可通过分布，有效的，无效的跨越水平的环境来启用，从而通过synevistion syers syers syers（1）索引（1.1）。和通信系统将增强当前的水下传感器的MI和光通信手段，整合了锚节点和AUV之间长距离通信的声学传输系统，并设计能量收集和补充解决方案，以延长水下传感器的寿命（30多年）； （2）通过多个AUV的分布和无处不在的数据传递，该数据旨在通过使用铁氧体的材料和三轴诱导天线来收集分布式数据并在整个水下网络中普遍存在，并将它们安装在AUV身体外，以增强MI的增强，并增强了多个AUVS的算法，并开发了多个Auvs的算法，以不良的功能功能不佳，等等，等等，等等，等等，等等，等等，等等，等等; （3）数据传输的效率和安全性，该效率和安全性设计网络算法以提高数据传输的效率和安全性。 AUV选择了一些传感器，而不是通过声音通信从每个传感器中收集数据，而是在近场（例如光线）中收集具有高数据速率传输模式的数据，并允许传感器远离AUV，从而通过MI/Light Commusications通过声波直接通过声波将数据直接发送到AUV。还将制定安全的数据传递方案，不仅可以保护数据传递免受典型的恶意攻击并保证收集到的数据的完整性，而且还允许在不知道他人的私人业务信息的情况下对一个业务实体的数据汇总； （4）实验验证和测试将验证提出的数据传递方案，并根据现有设施的模拟，实验和现场测试来定量地介绍性能提高。

项目成果

Robotic Harvesting of a Moving Swarm Represented by a Markov Process

以马尔可夫过程为代表的移动群体的机器人收获

• DOI: 10.1109/coase.2019.8843164
• 发表时间: 2019
• 期刊: Reshaping Particle Configurations by Collisions with Rigid Objects
• 作者: Bhatnagar, Shriya;Soto, Steban;Garcia, Javier;Becker, Aaron T.
• 通讯作者: Becker, Aaron T.

Pipe Data Through the Water: Stress Wave Communications Along Pipelines

• DOI: 10.1145/3366486.3366508
• 发表时间: 2019-10
• 期刊: Proceedings of the 14th International Conference on Underwater Networks & Systems
• 作者: Debing Wei;Chaoxian Qi;Jiefu Chen;A. Song;G. Song;M. Pan

Underwater Robot Localization Using Magnetic Induction: Noise Modeling and Hardware Validation

• DOI: 10.1109/ieeeconf38699.2020.9389237
• 发表时间: 2020-01-01
• 期刊: GLOBAL OCEANS 2020: SINGAPORE - U.S. GULF COAST
• 作者: Garcia, Javier;Soto, Steban;Becker, Aaron T.
• 通讯作者: Becker, Aaron T.

ROV assisted magnetic induction communication field tests in underwater environments

• DOI: 10.1145/3291940.3291988
• 发表时间: 2018-12
• 期刊: Proceedings of the 13th International Conference on Underwater Networks & Systems
• 作者: Debing Wei;S. Soto;Javier Garcia;Aaron T. Becker;Li Wang;M. Pan

COVID-19 Vulnerability Map Construction via Location Privacy Preserving Mobile Crowdsourcing

• DOI: 10.1109/globecom42002.2020.9348141
• 发表时间: 2020-12
• 期刊: GLOBECOM 2020 - 2020 IEEE Global Communications Conference
• 作者: Rui Chen;Liang Li;Jeffrey Jiarui Chen;Ronghui Hou;Yanmin Gong;Yuanxiong Guo;M. Pan