CPS: Breakthrough: Distributed Computing Under Uncertainty: A New Paradigm for Cooperative Cyber-Physical Systems
Lead PI:
Nicola Elia
Abstract
This project is to develop a dynamical systems model of distributed computation motivated from recent work on the distributed computation of averages. The key idea is that static optimization problems (particularly convex optimization problems) can be solved by designing a dynamic system that stabilizes around the optimal solution of the problem. Moreover, when the optimization problem is separable, then the designed dynamic system decomposes into a set of locally-interacting dynamic systems. This is expected to open a door to a host of new computational approaches that take advantage of recent developments in control engineering including robust control (providing a mechanism for errors introduced by discretization), Markovian Jump Linear Systems (providing a mechanism for random discretization time), event-driven control (providing a mechanism for assured asynchronous execution), control over networks (providing a mechanism for improved performance of distributed computational systems in general). The new approach is essential in emerging applications, where the optimization runs on physically separated agents, operating in a noisy environment and communicating over unreliable channels. As a test bed, the project will make use of a two-vehicle robotic system developed by the PI designed to monitor a crop of corn plants, where the dynamic systems perspective of this grant will, for example, allow for distributed optimal estimation toward the goal of optimal station-keeping. By studying how natural systems can collectively compute and optimize, this research has potential to impact many disciplines involving networked systems, from controlling the electric power grid, to modeling the behavior of social, biological or economic systems. It is directly applicable to cooperative networked multi-agent systems like robotic search and rescue missions and disaster-relief operations, distributed machine learning problems, and intelligent systems. An intriguing mix of motivating applications and theoretical problems offer a unique multidisciplinary educational opportunity to students who will be involved in the project, and provide exciting innovative material for courses and labs. Software developed will be distributed as open source via the CPS Virtual Organization.
Performance Period: 01/01/2013 - 12/31/2015
Institution: Iowa State University
Sponsor: National Science Foundation
Award Number: 1239319
CPS: Synergy: Collaborative Research: Hybrid Control Tools for Power Management and Optimization in Cyber-Physical Systems
Lead PI:
Magnus Egerstedt
Co-PI:
Sudhakar Yalamanchili
Yorai Wardi
Abstract
This project explores balancing performance considerations and power consumption in cyber-physical systems, through algorithms that switch among different modes of operation (e.g., low-power/high-power, on/off, or mobile/static) in response to environmental conditions. The main theoretical contribution is a computational, hybrid optimal control framework that is connected to a number of relevant target applications where physical modeling, control design, and software architectures all constitute important components. The fundamental research in this program advances state-of-the-art along four different dimensions, namely (1) real-time, hybrid optimal control algorithms for power management, (2) power-management in mobile sensor networks, (3) distributed power-aware architectures for infrastructure management, and (4) power-management in embedded multi-core processors. The expected outcome, which is to enable low-power devices to be deployed in a more effective manner, has implications on a number of application domains, including distributed sensor and communication networks, and intelligent and efficient buildings. The team represents both a research university (Georgia Institute of Technology) and an undergraduate teaching university (York College of Pennsylvania) in order to ensure that the educational components are far-reaching and cut across traditional educational boundaries. The project involves novel, inductive-based learning modules, where graduate students team with undergraduate researchers.
Performance Period: 10/01/2012 - 09/30/2015
Institution: Georgia Tech Research Corporation
Sponsor: National Science Foundation
Award Number: 1239225
Project URL
Project URL
CPS: Synergy: Collaborative Research: A Cyber-Physical Infrastructure for the "Smart City"
Lead PI:
Christos Cassandras
Co-PI:
Assaf J. Kfoury
Azer Bestavros
Yannis Paschalidis
Abstract
The project aims at making cities "smarter" by engineering processes such as traffic control, efficient parking services, and new urban activities such as recharging electric vehicles. To that end, the research will study the components needed to establish a Cyber-Physical Infrastructure for urban environments and address fundamental problems that involve data collection, resource allocation, real-time decision making, safety, and security. Accordingly, the research is organized along two main directions: (i) Sensing and data acquisition using a new mobile sensor network paradigm designed for urban environments; and (ii) Decision Support for the "Smart City" relying on formal verification and certification methods coupled with innovative dynamic optimization techniques used for decision making and resource allocation. The work will bring together and build upon methodological advances in optimization under uncertainty, computer simulation, discrete event and hybrid systems, control and games, system security, and formal verification and safety. Target applications include: a "Smart Parking" system where parking spaces are optimally assigned and reserved, and vehicular traffic regulation. The research has the potential of revolutionizing the way cities are viewed: from a passive living and working environment to a highly dynamic one with new ways to deal with transportation, energy, and safety. Teaming up with stakeholders in the Boston Back Bay neighborhood, the City of Boston, and private industry, the research team expects to establish new collaborative models between universities and urban groups for cutting-edge research embedded in the deployment of an exciting technological, economic, and sociological development.
Christos Cassandras

Christos G. Cassandras is Head of the Division of Systems Engineering and Professor of Electrical and Computer Engineering at Boston University. He is also co-founder of Boston University’s Center for Information and Systems Engineering (CISE). He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In 1982-84 he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In 1984-1996 he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, stochastic optimization, and computer simulation, with applications to computer and sensor networks, manufacturing systems, and transportation systems. He has published over 300 refereed papers in these areas, and five books. He has guest-edited several technical journal issues and serves on several journal Editorial Boards. He has recently collaborated with The MathWorks, Inc. in the development of the discrete event and hybrid system simulator SimEvents.

      Dr. Cassandras was Editor-in-Chief of the IEEE Transactions on Automatic Control from 1998 through 2009 and has also served as Editor for Technical Notes and Correspondence and Associate Editor. He is the 2012 President of the IEEE Control Systems Society (CSS) and has served as Vice President for Publications and on the Board of Governors of the CSS. He has chaired the CSS Technical Committee on Control Theory, and served as Chair of several conferences. He has been a plenary speaker at many international conferences, including the American Control Conference in 2001 and the IEEE Conference on Decision and Control in 2002, and an IEEE Distinguished Lecturer.

      He is the recipient of several awards, including the 2011 IEEE Control Systems Technology Award, the Distinguished Member Award of the IEEE Control Systems Society (2006), the 1999 Harold Chestnut Prize (IFAC Best Control Engineering Textbook) for Discrete Event Systems: Modeling and Performance Analysis, a 2011 prize for the IBM/IEEE Smarter Planet Challenge competition, a 1991 Lilly Fellowship and a 2012 Kern Fellowship. He is a member of Phi Beta Kappa and Tau Beta Pi. He is also a Fellow of the IEEE and a Fellow of the IFAC.

Performance Period: 10/01/2012 - 09/30/2015
Institution: Trustees of Boston University
Sponsor: National Science Foundation
Award Number: 1239021
Project URL
Project URL
CPS: Synergy: Collaborative Research: Coordinated Resource Management of Cyber-Physical-Social Power Systems
Lead PI:
Duncan Callaway
Co-PI:
Pravin Varaiya
Kameshwar Poolla
Abstract
Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid. The project integrates ideas from economics and behavioral science into frameworks grounded in control theory and power systems. Our central construct is that of a ?resource cluster,? a collection of distributed resources (ex: solar PV, storage, deferrable loads) that can be coordinated to efficiently and reliably offer services (ex: power delivery) in the face of uncertainty (ex: PV output, consumer behavior). Three topic areas form the core of the project: (a) the theoretical foundations for the ?cluster manager? concept and complementary tools to characterize the capabilities of a resource cluster; (b) centralized resource coordination strategies that span multiple time scales via innovations in stochastic optimal control theory; and (c) decentralized coordination strategies based on cluster manager incentives and built upon foundations of non-cooperative dynamic game theory. These innovations will improve the operation of infrastructure systems via a cyber-physical-social approach to the problem of resource allocation in complex infrastructures. By transforming the role of humans from passive resource recipients to active participants in the electric power system, the project will facilitate energy security for the nation, and climate change mitigation. The project will also engage K-12 students through lab-visits and lectures; address the undergraduate demand for power systems training through curricular innovations at the intersection of cyber-systems engineering and physical power systems; and equip graduate students with the multi-disciplinary training in power systems, communications, control, optimization and economics to become leaders in innovation.
Performance Period: 11/01/2012 - 10/31/2015
Institution: University of California-Berkeley
Sponsor: National Science Foundation
Award Number: 1239467
CPS: Synergy: Cyber Enabled Manufacturing Systems (CeMs) for Small Lot Manufacture
Lead PI:
Joseph Beaman
Co-PI:
Al Mok
Robert Moser
Omar Ghattas
Jayathi Murthy
Abstract
This grant provides funding for the development of Cyber Enabled Manufacturing (CeMs) process control for small lot manufacturing that incorporates a model of the process directly into the control algorithm. Such a model can be used to accommodate changes in the physical product and the manufacturing process and thus the manufacturing monitoring and control algorithm, so that changing conditions are easily accommodated without extensive additional experiments. A set of objectives of this physics and cyber-enabled manufacturing process control system are rational setting of manufacturing tolerances, real time prediction of manufacturing defects, real time control of process to eliminate defects, and real time monitoring and control for small lot manufacturing. The methodologies we propose to achieve these goals are high fidelity, physics based models including models of faults/defects, uncertainty quantification, reduced order models that run in real time, measurement, real time prediction, real time computer architecture, real time control with inverse solutions, and automating the CeMs process for generic manufacturing processes If successful, the results of this research will greatly reduce cycle time in producing new or modified products and improve the quality of manufacturing processes with accompanying reduction in waste, energy use, and cost. The development of such accurate control algorithms and their application to manufacturing processes can provide a competitive edge to US manufacturers. Perhaps more importantly, the education of engineers involved this research will supply US industry with employees who can apply this technology to many industrial processes.
Performance Period: 10/01/2012 - 09/30/2016
Institution: University of Texas at Austin
Sponsor: National Science Foundation
Award Number: 1239343
CPS: Synergy: A Hybrid Detector Network for Nuclear and Radioactive Threat Detection
Lead PI:
Er-Wei Bai
Co-PI:
Soura Dasgupta
Raghuraman Mudumbai
Paul Raptis
Alexander Heiftetz
Abstract
The most compelling problem confronting detection of nuclear material in a large area is the level of manifest uncertainty. Furthermore, detection and localization problems involve nontrivial and nonlinear non-convex optimization often stuck at local minima. This project develops fundamentally new techniques by using cheap detectors for rough detection and localization, placing detectors to expunge local minima, achieving fast distributed localization with reduced communication overheads, simultaneously localizing multiple sources and optimally placing detectors and assisting in their autonomous self-organization. There is a growing recognition of the inadequacy of current capabilities with respect to nuclear material detection and localization in public events and areas. This project develops an integrated cyber-physical system for public protection against nuclear and radiological threats. Clearly the project addresses a national security issue. If successful, the contribution and results of the project likely open a new framework for detection or monitoring in a large area using a wireless detector network. One of the key aspects of this project is the inter-disciplinary training of our graduate and undergraduate students including female and minority students in the areas of signal processing, statistical methods, modeling and performance analysis. K-12 students are also targeted through the First competition and Project-Lead-The-Way that connects the College of Engineering at the University of Iowa to almost all high school students in Iowa. It is expected that the project will generate enthusiasm and interests in science, mathematics and engineering for high school students.
Performance Period: 10/01/2012 - 09/30/2017
Institution: University of Iowa
Sponsor: National Science Foundation
Award Number: 1239509

14th International Conference on Distributed Computing and Networking

Submitted by Anonymous on

CDCN is a premier international conference dedicated to addressing advances in Distributed Computing and Communication Networks. Over the years, ICDCN has become a leading forum for disseminating the latest research results in these fields. As in the past, ICDCN 2013 will be organized in two tracks: Distributed Computing and Networking, and will comprise a highly selective technical program consisting of refereed concise papers, panel discussions as well as focused workshops on emerging topics.

First International Workshop on Sustainable Monitoring through Cyber-Physical Systems (SuMo-CPS)

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Wireless sensor networks (WSNs) have recently provided the right technology for enabling cable free systems for environmental monitoring. These networks of collaborative sensor nodes are easily deployable, can be embedded into structures, placed on the human body, dispersed in water and on-land and, through wireless communications, provide easy data reporting.

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