| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | June 8, 2015 |
| Latest Amendment Date: | June 2, 2019 |
| Award Number: | 1453126 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Ralph Wachter
rwachter@nsf.gov (703)292-8950 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | June 15, 2015 |
| End Date: | May 31, 2020 (Estimated) |
| Total Intended Award Amount: | $400,000.00 |
| Total Awarded Amount to Date: | $400,000.00 |
| Funds Obligated to Date: |
FY 2016 = $80,000.00 FY 2017 = $80,000.00 FY 2018 = $80,000.00 FY 2019 = $80,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
77 MASSACHUSETTS AVE CAMBRIDGE MA US 02139-4301 (617)253-1000 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
MA US 02139-4301 |
| 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: |
01001617DB NSF RESEARCH & RELATED ACTIVIT 01001718DB NSF RESEARCH & RELATED ACTIVIT 01001819DB NSF RESEARCH & RELATED ACTIVIT 01001920DB NSF RESEARCH & RELATED ACTIVIT |
| 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
This project advances the scientific knowledge on design methods for improving the resilience of civil infrastructures to disruptions. To improve resilience, critical services in civil infrastructure sectors must utilize new diagnostic tools and control algorithms that ensure survivability in the presence of both security attacks and random faults, and also include the models of incentives of human decision makers in the design process. This project will develop a practical design toolkit and platform to enable the integration of resiliency-improving control tools and incentive schemes for Cyber-Physical Systems (CPS) deployed in civil infrastructures. Theory and algorithms will be applied to assess resiliency levels, select strategies to improve performance, and provide reliability and security guarantees for sector-specific CPS functionalities in water, electricity distribution and transportation infrastructures. The main focus is on resilient design of network control functionalities to address problems of incident response, demand management, and supply uncertainties. More broadly, the knowledge and tools from this project will influence CPS designs in water, transport, and energy sectors, and also be applicable to other systems such as supply-chains for food, oil and gas. The proposed platform will be used to develop case studies, test implementations, and design projects for supporting education and outreach activities.
Current CPS deployments lack integrated components designed to survive in uncertain environments subject to random events and the actions of strategic entities. The toolkit (i) models the propagation of disruptions due to failure of cyber-physical components, (ii) detects and responds to both local and network-level failures, and (iii) designs incentive schemes that improve aggregate levels of public good (e.g., decongestion, security), while accounting for network interdependencies and private information among strategic entities. The validation approach uses real-world data collected from public sources, test cases developed by domain experts, and simulation software. These tools are integrated to provide a multi-layer design platform, which explores the design space to synthesize solutions that meet resiliency specifications. The platform ensures that synthesized implementations meet functionality requirements, and also estimates the performance guarantees necessary for CPS resilience. This modeling, validation, exploration, and synthesis approach provides a scientific basis for resilience engineering. It supports CPS education by providing a platform and structured workflow for future engineers to approach and appreciate implementation realities and socio-technical constraints.
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 NSF CAREER project advanced the PI's research and teaching in control of infrastructure systems, applied game theory, and optimization in networks. The main focus was on three main topics: (1) Resilient Network Control, (2) Information Systems in Strategic Environments, and (3) Optimal Resource Allocation. The project contributed to modeling foundations and computational tools that are needed for improving the performance of large-scale critical infrastructure systems in the face of disruptions, both stochastic and adversarial. The research was grounded in the domains of highway transportation, electric power distribution, and urban water and gas networks. The PI mentored 5 PhD students and also supervised a number of Masters theses.
The research on resilient network control aims to design operational strategies that maintain system performance under disturbances caused by random incidents or adversarial attacks. We address questions about problems in highway traffic operations such as the effects of capacity perturbations on the stability of traffic queues and system throughput, operation of autonomous vehicle platoons in mixed traffic, and incident-aware ramp metering. We also studied a generic security game to analyze strategic interdiction by an agency (operator) who wants to optimally intercept the flow of illegal goods through a capacitated transportation network.
The work on information systems in strategic environments examines the effects of heterogeneities in information access and accuracy on the equilibrium behavior of user populations, and consequently, the impacts to network efficiency. Our research in Bayesian congestion games systematically analyzes the relative value of heterogeneous traffic information systems for traveler populations who have incomplete and asymmetric information about the network state and other travelers. We also model the incentives of strategic misbehavior by users (customers) served by an infrastructure utility when they misreport their true "type" to the utility. We identify the utility's optimal inspection strategies for limiting its loss due to the actions of misbehaving users.
In optimal resource allocation, we design algorithms for strategic positioning of sensing resources in large-scale pipeline networks (e.g. water and natural gas) to obtain detection guarantees against multiple strategic failure events. We also study the value of proactive defense investments for securing multiple infrastructure facilities with different levels of criticality as the technological costs of attack and defense vary. To improve the resilience of electricity distribution networks against correlated failures (particularly, remote attacks and storm-induced disruptions), we investigate the use of microgrid operations and allocation/dispatch of low-inertia distributed energy resources.
Teaching has been a truly enjoyable and rewarding experience for the PI. His courses aim to make students effectively use system-theoretic concepts in modeling, analysis, and control of large-scale infrastructure systems. His goal is to help students acquire fundamental knowledge in network modeling, optimization methods, control theory, and game-theoretic analysis so that they become trained users of these techniques for infrastructure applications. He includes numerous case studies in his courses, and all students are required to have a computational aspect their course projects. Resilient Networks is his signature graduate course. It attracts students from a variety of disciplines such as transportation, systems, computational engineering, and operations research. The course covers a wide range of topics, highlights recent developments in resilience of cyber-physical systems, and also presents open questions and areas of ongoing research. He has also been teaching Engineering Sustainability to undergraduate students majoring in civil systems. This course introduces the beauty of mathematical modeling and systems thinking to undergraduate students so that they can effectively use these skills in their profession. In addition, the PI has enjoyed mentoring several undergraduate students for their senior year capstone design and SuperUROP projects. Finally, the PI supervised Masters theses of several students in the MIT Leaders of Global Operations (LGO) program.
Last Modified: 08/03/2020
Modified by: Saurabh Amin
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