
NSF Org: |
CNS Division Of Computer and Network Systems |
Recipient: |
|
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 2017 = $16,000.00 FY 2018 = $8,000.00 |
History of Investigator: |
|
Recipient Sponsored Research Office: |
4300 MARTIN LUTHER KING BLVD HOUSTON TX US 77204-3067 (713)743-5773 |
Sponsor Congressional District: |
|
Primary Place of Performance: |
4302 University Drive, Room 316 Houston TX US 77204-2015 |
Primary Place of
Performance Congressional District: |
|
Unique Entity Identifier (UEI): |
|
Parent UEI: |
|
NSF Program(s): |
Special Projects - CNS, CPS-Cyber-Physical Systems |
Primary Program Source: |
01001819DB NSF RESEARCH & RELATED ACTIVIT 01001718DB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): |
|
Program Element Code(s): |
|
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
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external
site maintained by the publisher. Some full text articles may not yet be available without a
charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from
this site.
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
Please report errors in award information by writing to: awardsearch@nsf.gov.