Award Abstract # 1646607
CPS: Synergy: Collaborative Research: DEUS: Distributed, Efficient, Ubiquitous and Secure Data Delivery Using Autonomous Underwater Vehicles

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: UNIVERSITY OF HOUSTON SYSTEM
Initial Amendment Date: September 7, 2016
Latest Amendment Date: May 31, 2018
Award Number: 1646607
Award Instrument: Standard Grant
Program Manager: Sylvia Spengler
sspengle@nsf.gov
 (703)292-7347
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: January 1, 2017
End Date: December 31, 2020 (Estimated)
Total Intended Award Amount: $600,000.00
Total Awarded Amount to Date: $624,000.00
Funds Obligated to Date: FY 2016 = $600,000.00
FY 2017 = $16,000.00

FY 2018 = $8,000.00
History of Investigator:
  • Miao Pan (Principal Investigator)
    mpan2@uh.edu
  • Jiefu Chen (Co-Principal Investigator)
  • Zhu Han (Co-Principal Investigator)
  • Aaron Becker (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Houston
4300 MARTIN LUTHER KING BLVD
HOUSTON
TX  US  77204-3067
(713)743-5773
Sponsor Congressional District: 18
Primary Place of Performance: University of Houston
4302 University Drive, Room 316
Houston
TX  US  77204-2015
Primary Place of Performance
Congressional District:
18
Unique Entity Identifier (UEI): QKWEF8XLMTT3
Parent UEI:
NSF Program(s): Special Projects - CNS,
CPS-Cyber-Physical Systems
Primary Program Source: 01001617DB NSF RESEARCH & RELATED ACTIVIT
01001819DB NSF RESEARCH & RELATED ACTIVIT

01001718DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 8235, 7918, 9251
Program Element Code(s): 171400, 791800
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 22)
Wei, Debing and Yan, Li and Li, Xuanheng and Sun, Yi and Yuan, Dongfeng and Chen, Jiefu and Pan, Miao "Exploiting Magnetic Field Analysis to Characterize MI Wireless Communications in Subsea Environments" 2018 International Conference on Computing, Networking and Communications (ICNC) , 2018 10.1109/ICCNC.2018.8390295 Citation Details
Wei, Debing and Soto, Steban S. and Garcia, Javier and Becker, Aaron T. and Wang, Li and Pan, Miao "ROV assisted magnetic induction communication field tests in underwater environments" WUWNet '18 Proceedings of the Thirteenth ACM International Conference on Underwater Networks & Systems , 2017 10.1145/3291940.3291988 Citation Details
Nguyen, An and Krupke, Dominik and Burbage, Mary and Bhatnagar, Shriya and Fekete, Sandor P. and Becker, Aaron T. "Using a UAV for Destructive Surveys of Mosquito Population" 2018 IEEE International Conference on Robotics and Automation (ICRA) , 2018 10.1109/ICRA.2018.8463184 Citation Details
Qi, Chaoxian and Wei, Debing and Pan, Miao and Chen, Jiefu "Underwater Wireless Communication Using Coil-Based Magnetic Induction" 2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium) , 2020 https://doi.org/10.23919/USNC/URSI49741.2020.9321593 Citation Details
Shell, Dylan A. and Huang, Li and Becker, Aaron T. and O'Kane, Jason M. "Planning Coordinated Event Observation for Structured Narratives" Planning Coordinated Event Observation for Structured Narratives , 2019 https://doi.org/10.1109/ICRA.2019.8794450 Citation Details
Su, Chunxia and Ye, Fang and Wang, Li-Chun and Wang, Li and Tian, Yuan and Han, Zhu "UAV-Assisted Wireless Charging for Energy-Constrained IoT Devices Using Dynamic Matching" IEEE Internet of Things Journal , v.7 , 2020 https://doi.org/10.1109/JIOT.2020.2968346 Citation Details
Baez, Victor M. and Poyrekar, Shreyas and Ibarra, Marcos and Haikal, Yusef and Jafari, Navid H. and Becker, Aaron T. "Wetland Soil Strength Tester and Core Sampler Using a Drone" 2021 IEEE International Conference on Robotics and Automation (ICRA) , 2021 https://doi.org/10.1109/ICRA48506.2021.9561234 Citation Details
Baez, Victor M. and Shah, Ami and Akinwande, Samuel and Jafari, Navid H. and Becker, Aaron T. "Assessment of Soil Strength using a Robotically Deployed and Retrieved Penetrometer" 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020 https://doi.org/10.1109/IROS45743.2020.9341424 Citation Details
Becker, Aaron T. and Debboun, Mustapha and Fekete, S{\'a}ndor P. and Krupke, Dominik and Nguyen, An "Zapping Zika with a Mosquito-Managing Drone: Computing Optimal Flight Patterns with Minimum Turn Cost (Multimedia Contribution)" 33rd International Symposium on Computational Geometry (SoCG 2017) , v.77 , 2017 10.4230/LIPIcs.SoCG.2017.62 Citation Details
Bhatnagar, Shriya and Soto, Steban and Garcia, Javier and Becker, Aaron T. "Robotic Harvesting of a Moving Swarm Represented by a Markov Process" Reshaping Particle Configurations by Collisions with Rigid Objects , 2019 10.1109/COASE.2019.8843164 Citation Details
Chen, Rui and Li, Liang and Chen, Jeffrey Jiarui and Hou, Ronghui and Gong, Yanmin and Guo, Yuanxiong and Pan, Miao "COVID-19 Vulnerability Map Construction via Location Privacy Preserving Mobile Crowdsourcing" 2020 IEEE Global Communications Conference , 2020 https://doi.org/10.1109/GLOBECOM42002.2020.9348141 Citation Details
(Showing: 1 - 10 of 22)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

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 proposes a viable cyber interconnection scheme that enables distributed, efficient, ubiquitous, and secure (DEUS) data delivery is therefore in dire need.

 

In this project, an integrated cyber-physical system (CPS) scheme has been developed to facilitate data delivery from subsea sensors to the ocean surface. The CPS scheme is featured by ferrite enhanced magnetic-induction (MI) conformal antenna designs for autonomous underwater vehicles (AUVs), MI based subsea wireless communications, AUVs assisted data delivery, and subsea hybrid wireless networking and internet of things (IoT). The transformative and interdisciplinary nature of this project's research outcomes will advance the knowledge of underwater wireless communications and networking, robotic design and control, and can potentially be used by industry for underwater IoT development. Correspondingly, the research outcomes have impact on people's daily lives and further provide greater opportunities for job creation and economic growth.

 

Together with a few other NSF sponsored projects, this project has supported multiple graduate students including five female PhD students (3 from PI Pan's team, 1 from Co-PI Chen's team, and 1 from Co-PI Becker's team) and several Hispanic students (from PI Pan and Co-PI Becker's teams). Particularly, PI Pan’s two female students partially working on this project have graduated as PhD, and become assistant professors in electrical engineering and/or computer science departments in universities after their graduation, continuing to train the next generation national work force. Multiple MS students and REU students sponsored by this project continue their PhD study at UH after their graduation. The results of this project have also been disseminated through publications in technical journals, keynote speeches and presentations at conferences, and invited talks at both national and international institutions.


Last Modified: 04/06/2021
Modified by: Miao Pan

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