The objective of this research is to develop non-volatile computing devices, which allow the power source to be cut off at any time, and yet resume regular operation without loss of information when the power comes back. The approach is to replace all critical memory components with non-volatile units so that computing state is maintained over power interruptions. The advancement in new Flash memory devices makes this approach feasible by enabling low-voltage program/erase (P/E) around ±2V and a long (projected >1016) cycling endurance to be integrated into CMOS technology. This research effort seeks to establish a new paradigm of computing where non-volatile memory units are used pervasively to enhance reliability against power source instability, energy-efficiency, and security. The non-volatile computing devices are especially useful for embedded cyber-physical systems enabling long running computations and data collection even with unreliable power sources. The technologies developed from this project can also benefit conventional architecture in its power optimization and internal security code generation. The project is a close collaboration between computer architecture and CMOS technology development groups, where all levels in the design hierarchy will be visited for system and technology evaluation. This project integrates its research efforts with education by developing an undergraduate and Master curriculum that spans over the vertical design hierarchy in microprocessors. This vertical education will better prepare future work force in tackling tremendous design challenges spanning many layers of microprocessors. The results from this project will be made widely available to both industry and academia.

Objectives and approaches. The objective of this research is to create a novel Cyber-Physical System, a self-reconfiguring ?second skin orthotic sleeve? consisting of programmable materials. The orthotic sleeve, worn over one or more limbs of brain-injured individuals, may restore brain function by promoting enriched exploration of self-produced limb movements. The approach consists of three steps (1) micro-fabricating sheets with embedded sensors and muscle-like collections of force-producing actuators, (2) conducting longitudinal recordings of kicking by typically developing and preterm brain-injured infants who wear a sensing, but not actuated micro-fabricated second skin, and (3) developing biologically-inspired programming techniques to help determine an algorithm with which the second skin embedded actuators may adaptively assist the ever-changing developmental pattern of infant kicking. The technology can be applied to many mobility-impaired populations,including children and adults with brain injury, the ageing population, and injured soldiers. The project will inform basic scientific and engineering research in areas such as formation of architectural structures by large-scale multi-agent robotic systems, and self-organization of swarming small-scale agents that act autonomously in cooperation with biological systems. The multi-institutional effort of this research endeavor will positively impact undergraduate and graduate science education via explorations of the intersection of biology and computation in cyber-physical systems. Innovation, teamwork, and the value of communication are encouraged. These efforts will promote education of an American work force that is technically expert, scientifically comprehensive, and socially aware to sustain national excellence in a future increasingly based on technologically complex systems.

The objective of this research is to investigate and implement a software architecture to improve productivity in the development of rapidly deployable, robust, real-time situational awareness and response applications. The approach is based on a modular cross-layered architecture that combines a data-centric descriptive programming model with an overlay-based communication model. The cross-layer architecture will promote an efficient implementation. Simultaneously, the data-centric programming model and overlay-based communication model will promote a robust implementation that can take advantage of heterogeneous resources and respond to different failures. There is currently no high-level software architecture that meets the stringent requirements of many situational awareness and response applications. The proposed project will fill this void by developing a novel data-centric programming model that spans devices with varying computational and communication capabilities. Similarly, the overlay communication model will extend existing work by integrating network resources with the programming model. This cross-layer design will promote the implementation of efficient and robust applications. This research will benefit society by providing emergency responders with software tools that present key information in a timely fashion. This, in turn, will increase safety and reduce economic and human loss during emergencies. The productivity gains in deploying sensors and mobile devices will benefit other domains, such as field research using sensor networks. Software will be released under an open-source license to promote the use by government agencies, research institutions, and individuals. Products of this research, including the software, will be used in courses at the University of North Carolina.

The objective of this research is to develop energy-efficient integrity establishment techniques for dynamic networks of cyber physical devices. In such dynamic networks, devices connect opportunistically and perform general-purpose computations on behalf of other devices. However, some devices may be malicious in intent and affect the integrity of computation. The approach is to develop new trust establishment mechanisms for dynamic networks. Existing trusted computing mechanisms are not directly applicable to cyber physical devices because they are resource-intensive and require devices to have special-purpose hardware. This project is addressing these problems along three research prongs. The first is a comprehensive study of the resource bottlenecks in current trust establishment protocols. Second, the insights from this study are being used to develop resource-aware attestation protocols for cyber physical devices that are equipped with trusted hardware. Third, the project is developing new trust establishment protocols for cyber physical devices that may lack trusted hardware. A key outcome of the project is an improved understanding of the tradeoffs needed to balance the concerns of security and resource-awareness in dynamic networks. Dynamic networks allow cyber physical devices to form a highly-distributed, cloud-like infrastructure for computations involving the physical world. The trust-establishment mechanisms developed in this project encourage devices to participate in dynamic networks, thereby unleashing the full potential of dynamic networks. This project includes development of dynamic networking applications, such as distributed gaming and social networking, in undergraduate curricula and course projects, thereby fostering the participation of this key demographic.

The objective of this research is to address fundamental challenges in the verification and analysis of reconfigurable distributed hybrid control systems. These occur frequently whenever control decisions for a continuous plant depend on the actions and state of other participants. They are not supported by verification technology today. The approach advocated here is to develop strictly compositional proof-based verification techniques to close this analytic gap in cyber-physical system design and to overcome scalability issues. This project develops techniques using symbolic invariants for differential equations to address the analytic gap between nonlinear applications and present verification techniques for linear dynamics. This project aims at transformative research changing the scope of systems that can be analyzed. The proposed research develops a compositional proof-based approach to hybrid systems verification in contrast to the dominant automata-based verification approaches. It represents a major improvement addressing the challenges of composition, reconfiguration, and nonlinearity in system models The proposed research has significant applications in the verification of safety-critical properties in next generation cyber-physical systems. This includes distributed car control, robotic swarms, and unmanned aerial vehicle cooperation schemes to full collision avoidance protocols for multiple aircraft. Analysis tools for distributed hybrid systems have a broad range of applications of varying degrees of safety-criticality, validation cost, and operative risk. Analytic techniques that find bugs or ensure correct functioning can save lives and money, and therefore are likely to have substantial economic and societal impact.

The objective of this research is to investigate the foundations, methodologies, algorithms and implementations of cyberphysical networks in the context of medical applications. The approach is to design, implement and study Carenet, a medical care network, by investigating three critical issues in the design and construction of cyberphysical networks: (1) rare event detection and multidimensional analysis in cyberphysical data streams, (2) reliable and trusted data analysis with cyberphysical networks, including veracity analysis for object consolidation and redundancy elimination, entity resolution and information integration, and feedback interaction between cyber- and physical- networks, and (3) spatiotemporal data analysis including spatiotemporal cluster analysis, sequential pattern mining, and evolution of cyberphysical networks. Intellectual merit: This project focuses on several most pressing issues in large-scale cyberphysical networks, and develops foundations, principles, methods, and technologies of cyberphysical networks. It will deepen our understanding of the foundations, develop effective and scalable methods for mining such networks, enrich our understanding of cyberphysical systems, and benefit many mission-critical applications. The study will enrich the principles and technologies of both cyberphysical systems and information network mining. Broader impacts: The project will integrate multiple disciplines, including networked cyberphysical systems, data mining, and information network technology, and advance these frontiers. It will turn raw data into useful knowledge and facilitate strategically important applications, including the analysis of patient networks, combat networks, and traffic networks. Moreover, the project systematically generates new knowledge and contains a comprehensive education and training plan to promote diversity, publicity, and outreach.

The objective of this research is to investigate the foundations, methodologies, algorithms and implementations of cyberphysical networks in the context of medical applications. The approach is to design, implement and study Carenet, a medical care network, by investigating three critical issues in the design and construction of cyberphysical networks: (1) rare event detection and multidimensional analysis in cyberphysical data streams, (2) reliable and trusted data analysis with cyberphysical networks, including veracity analysis for object consolidation and redundancy elimination, entity resolution and information integration, and feedback interaction between cyber- and physical- networks, and (3) spatiotemporal data analysis including spatiotemporal cluster analysis, sequential pattern mining, and evolution of cyberphysical networks. Intellectual merit: This project focuses on several most pressing issues in large-scale cyberphysical networks, and develops foundations, principles, methods, and technologies of cyberphysical networks. It will deepen our understanding of the foundations, develop effective and scalable methods for mining such networks, enrich our understanding of cyberphysical systems, and benefit many mission-critical applications. The study will enrich the principles and technologies of both cyberphysical systems and information network mining. Broader impacts: The project will integrate multiple disciplines, including networked cyberphysical systems, data mining, and information network technology, and advance these frontiers. It will turn raw data into useful knowledge and facilitate strategically important applications, including the analysis of patient networks, combat networks, and traffic networks. Moreover, the project systematically generates new knowledge and contains a comprehensive education and training plan to promote diversity, publicity, and outreach.

The objective of this research is to develop numerical techniques for solving partial differential equations (PDE) that govern information flow in dense wireless networks. Despite the analogy of information flow in these networks to physical phenomena such as thermodynamics and fluid mechanics, many physical and protocol imposed constraints make information flow PDEs unique and different from the observed PDEs in physical phenomena. The approach is to develop a systematic method where a unified framework is capable of optimizing a broad class of objective functions on the information flow in a network of a massive number of nodes. The objective function is defined depending on desired property of the geometric paths of information. This leads to PDEs whose form varies depending on the optimization objective. Finally, numerical techniques will be developed to solve the PDEs in a network setting and in a distributed manner. The intellectual merits of this project are: developing mathematical tools that address a broad range of design objectives in large scale wireless sensor networks under a unified framework; initiating a new field on numerical analysis of information flow in dense wireless networks; and developing design tools for networking problems such as transport capacity, routing, and load balancing. The broader impacts of this research are: helping the development of next generation wireless networks; encouraging involvement of undergraduate students and underrepresented groups, and incorporating the research results into graduate level courses. Additionally, the research is interdisciplinary, bringing together sensor networking, theoretical physics, partial differential equations, and numerical optimization.

The objectives of this research are to design a heterogeneous network of embedded systems so that faults can be quickly detected and isolated and to develop on-line and off-line fault diagnosis and prognosis methods. Our approach is to develop functional dependency models between the failure modes and the concomitant monitoring mechanisms, which form the basis for failure modes, effects and criticality analysis, design for testability, diagnostic inference, and the remaining useful life estimation of (hardware) components. Over the last few years, the electronic explosion in automotive vehicles and other application domains has significantly increased the complexity, heterogeneity, and interconnectedness of embedded systems. To address the cross-subsystem malfunction phenomena in such networked systems, it is essential to develop a common methodology that: (i) identifies the potential failure modes associated with software, hardware, and hardware-software interfaces; (ii) generates functional dependencies between the failure modes and tests; (iii) provides an on-line/off-line diagnosis system; (iv) computes the remaining useful life estimates of components based on the diagnosis; and (iv) validates the diagnostic and prognostic inference methods via fault injection prior to deployment in the field. The development of functional dependency models and diagnostic inference from these models to aid in online and remote diagnosis and prognosis of embedded systems is a potentially novel aspect of this effort. This project seeks to improve the competitiveness of the U.S. automotive industry by enhancing vehicle reliability, performance and safety, and by improving customer satisfaction. Other representative applications include aerospace systems, electrification of transportation, medical equipment, and communication and power networks, to name a few.

The objective of this research is to bring high levels of system reliability and integrity to application domains that cannot afford the cost, power, weight, and size associated with physical redundancy. The approach is to develop complementary monitoring algorithms and novel computing architectures that enable the detection of faults. In particular, there is a significant opportunity to reduce the reliance on physical redundancy by combining model-based and data-driven monitoring techniques. Implementing this approach to fault detection would be difficult with existing software and computing architectures. This motivates the development of a general purpose monitoring framework through monitoring-aware compilers coupled with enhancements to multi-core architectures. The intellectual merit of the project is twofold. First, it has the potential to lead to a novel fault detection approach that blends complementary monitoring algorithms. Second, advances in multi-core processors are leveraged to enable implementation of these fault detection approaches. This addresses key themes in cyber-physical systems by investigating the fundamental issue of fault detection for physical systems and by developing a generic processor architecture for monitoring. With respect to broader impact, project offers the potential for positive influences on industrial practice and education. If successful, the design ideas from this project can be incorporated into low-cost multi-core architectures suitable for embedded systems. The potentially transformative performance improvement offered by this framework could also impact current research in run-time verification and on-line monitoring. The research is to be incorporated into the course "Design, Build, Simulate, Test and Fly Small Uninhabited Aerial Vehicles" for senior undergraduate and first-year graduate students.