| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 30, 2017 |
| Latest Amendment Date: | August 30, 2017 |
| Award Number: | 1739642 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Sankar Basu
sabasu@nsf.gov (703)292-7843 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | January 15, 2018 |
| End Date: | December 31, 2021 (Estimated) |
| Total Intended Award Amount: | $500,000.00 |
| Total Awarded Amount to Date: | $500,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
300 TURNER ST NW BLACKSBURG VA US 24060-3359 (540)231-5281 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1145 Perry St, 432 Durham (0350) Blacksburg VA US 24061-1019 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CPS-Cyber-Physical Systems |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Realizing the vision of pervasive Internet of Things (IoT) that will endow a myriad of physical objects that include sensors, wearables, mundane objects, and connected vehicles, with cyber capabilities, is contingent upon effectively managing the interwoven synergies across its cyber and physical realms. The overarching goal of this project is to develop a novel cyber-physical system (CPS) science that can enable effective modeling, optimization, and management of the IoT as a fully-fledged CPS. Developing this science will, in turn, catalyze the deployment of the IoT and its numerous services that range from smart healthcare, to smart buildings and intelligent transportation, thus having a broad societal impact. Enabling the IoT will also expedite the transformation of cities and communities, into truly smart environments thus enhancing the quality of life of their residents. The proposed research is coupled with an educational plan that includes substantial involvement of graduate and undergraduate students in cross-cutting CPS research, as well as IoT-centric outreach activities targeted at local high school students from the under-represented groups. This synergistic integration of research and education will contribute to training a new workforce that is equipped with the necessary CPS skills needed to work in the emerging IoT domains.
The proposed research will develop a foundational framework for the modeling and performance analysis of the IoT that will facilitate the management of resources, such as energy and computation, jointly across its cyber and physical realms. By leveraging interdisciplinary tools from stochastic geometry, distributed optimization, and operations research, the proposed framework will yield a number of results that include new statistical models and CPS performance metrics for characterizing the cyber-physical operation of IoT as well as novel distributed optimization algorithms that will adapt the cyber-physical operational state of the IoT devices to the dynamics of the CPS environment, while being cognizant of their stringent resource constraints. The developed theory will be validated using extensive simulations as well as basic experiments. The ensuing outcomes are expected to yield a fundamentally new CPS science that will transform the way in which the IoT is modeled, analyzed, and optimized. The foundational nature of this research will further ensure that its impacts will cut across multiple CPS domains, ranging from energy to transportation and healthcare.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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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.
This award has laid the foundations for the cyber-physical system (CPS) Internet of Things (IoT) by developing a transformative new framework that leverages synergies between its cyber and physical functions and turns them into system-wide efficiencies. By blending interdisciplinary tools from CPS, stochastic geometry, distributed optimization, control theory, and machine learning, this project has yielded a number of innovations related to the modeling, design, optimization, and management of a CPS IoT.
From the modeling and analysis perspective, this project has made major advances in developing models and metrics for CPS IoT that are cognizant of its cyber and physical functions. The massive scale of CPS IoT was captured by using ideas from stochastic geometry while the CPS metrics were built on the idea of age of information (AoI) which provides a rigorous way of characterizing the freshness of information in CPS IoT. A representative outcome of this direction of research was a comprehensive approach toward cyber-physical performance characterization of a wirelessly-powered CPS IoT in which the wireless transmissions from the same cyber-infrastructure network are used for energy harvesting and for providing wireless connectivity to the IoT devices. A representative outcome related to the CPS IoT metrics was a set of works on the characterization of the distributional properties of AoI in wirelessly-powered status updating systems that are an important subclass of CPS IoT. Given the importance of AoI-related metrics in a CPS IoT, their spatial distribution was also studied in a large-scale CPS IoT using stochastic geometry. This provided key insights into the differences between AoI and classical cyber-network metrics like system throughput. From the operational standpoint, this research provided new joint sampling and updating policies for different CPS IoT setups including drone-assisted IoT systems and wirelessly-powered IoT networks. Given the energy-constrained nature of some CPS IoT devices, the role of ambient backscatter communications in CPS IoT was also explored. This project also provided some of the first results on the joint design and optimization of the cyber and physical functions of a CPS IoT. A key effort in this regard included the analysis of achievable reliability for mobile CPS IoT systems such as autonomous vehicles while taking into account the cyber requirements (e.g., wireless latency) and the physical requirements (e.g., control system stability) jointly. A major outcome of this effort was a set of rigorous design guidelines on how to jointly design the wireless and control systems in order to ensure that the cyber-physical performance needs of both functions are satisfied. This joint cyber-physical design and optimization paradigm was then expanded to a plethora of applications including swarms of drones. In addition, the role of distributed learning as an optimization tool for joint cyber-physical design was explored across these applications. The key results here show how one can design CPS IoT-oriented learning algorithms that can harness the synergies across communication and control systems so as to enable the autonomous operation of CPS IoTs.
The foundational nature of this project led to broad impacts across multiple disciplines. This project trained multiple Ph.D. students on all aspects of this research. Two of them have already graduated and are enjoying strong careers in the industry. The key concepts of this research were integrated into local outreach events at Virginia Tech, including summer camps for middle school girls and freshman seminars. Results from this project were broadly disseminated through publications in top IEEE venues, tutorials, short courses, seminars, and invited lectures. The PIs were also actively involved in organizing workshops and editing journal special issues related to this broad topic. Research results from this project were also integrated into the graduate curriculum at Virginia Tech. The two PIs also collaborated on a book effort that led to the first edited book on the topic of AoI, which was naturally inspired and informed by this project.
Last Modified: 05/26/2022
Modified by: Harpreet S Dhillon
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