The objective of this research is the design of innovative routing, planning and coordination strategies for robot networks, and their application to oceanography. The approach is organized in three synergistic thrusts: (1) the application of queueing theory and combinatorial techniques to networked robots performing sequential tasks, (2) the design of novel distributed optimization and coordination schemes relying only on asynchronous and asymmetric communication, (3) the design of practical routing and coordination algorithms for the USC Networked Aquatic Platforms. In collaboration with oceanographers and marine biologists, the project aims to design motion, communication and interaction protocols that maximize the amount of scientific information collected by the platforms. This proposal addresses multi-dimensional problems of relevance in Engineering and Computer Science by unifying fundamental concepts from multiple cyberphysical domains (robotics, autonomy, combinatorics, and network science). Our team has expertise in a broad range of scientific disciplines, including control theory and theoretical computer science and their applications to multi-agent systems, robotics and sensor networks. The proposed research will have a positive impact on the emerging technology of autonomous and reliable robotic networks, performing a broad range of environmental monitoring and logistic tasks. Our educational and outreach objectives are manifold and focus on (1) integrating the proposed research themes into undergraduate education and research, e.g., via the existing NSF REU site at the USC Computer Science Department, and (2) mounting a vigorous program of outreach activities, e.g., via a well-developed collaboration with the UCSB Center for Science and Engineering Partnerships.

Abstract The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

The objective of this research is to develop a new approach for composition of safety-critical cyber-physical systems from a small code base of verified components and a large code base of unverified commercial off-the-shelf components. The approach is novel in that it does not require generating the entire code base from formal languages, specifications, or models and does not require verification to be applied to all code. Instead, an explicit goal is to accommodate large amounts of legacy code that is typically too complex to verify. The project introduces a set of verified component wrappers around existing unverified code, such that specified global system properties hold. The intellectual merit of the project lies in its innovative approach for managing component interactions. Unexpected interactions are the primary source of failure in cyber-physical systems. A fundamental conceptual challenge is to understand the different interaction spaces of cyber-physical system components and determine a set of trigger conditions when certain interactions must be restricted to prevent failure. The project develops analysis techniques that help understand the different interaction types and provides component wrappers to restrict them when necessary. Broader impact lies in significantly reducing the design and composition effort for the next generation of safety-critical embedded systems. A variety of student projects are being offered to undergraduates and graduate students. The researchers especially encourage women and minorities to participate. Outreach activity, such as hosting K-12 students on school field/science days, further strengthen the educational component. Technology transfer to John Deere is expected.

The objective of this research is to establish a new development paradigm that enables the effective design, implementation, and certification of medical device cyber-physical systems. The approach is to pursue the following research directions: 1) to support medical device interconnectivity and interoperability with network-enabled control; 2) to apply coordination between medical devices to support emerging clinical scenarios; 3) to ?close the loop? and enable feedback about the condition of the patient to the devices delivering therapy; and 4) to assure safety and effectiveness of interoperating medical devices. The intellectual merits of the project are 1) foundations for rigorous development, which include formalization of clinical scenarios, operational procedures, and architectures of medical device systems, as well as patient and caregiver modeling; 2) high-confidence software development for medical device systems that includes the safe and effective composition of clinical scenarios and devices into a dynamically assembled system; 3) validation and certification of medical device cyber-physical systems; and 4) education of the next-generation of medical device system developers who must be literate in both computational and physical aspects of devices. The broader impacts of the project will be achieved in three ways. Novel design methods and certification techniques will significantly improve patient safety. The introduction of closed-loop scenarios into clinical practice will reduce the burden that caregivers are currently facing and will have the potential of reducing the overall costs of health care. Finally, the educational efforts and outreach activities will increase awareness of careers in the area of medical device systems and help attract women and under-represented minorities to the field.

The objective of this research is to develop new foundations of composition in heterogeneous systems, to apply these foundations in a new generation of tools for system integration, and to validate the results in experiments using automotive and avionics System-of-Systems experimental platforms. The approach exploits simplification strategies: develop theories, methods, and tools to assist in inter-layer decoupling. The research program has three focus areas: (1) theory of compositionality in heterogeneous systems, (2) tools and tool architectures for system integration, and (3) systems/experimental research. The project develops and deploys theories and methods for inter-layer decoupling that prevent or decrease the formation of intractable system-wide interdependences and maintain compositionality at each layer for carefully selected, essential system properties. Compositionality in tools is sought by exploring semantic foundations for model-based design. Systems/experimental research is conducted in collaboration with General Motors Global R&D (GM) and focuses on electric car platforms. The project is contributing to the cost effective development and deployment of many safety and security-critical cyber-physical systems, ranging from medical devices to transportation, to defense and avionics. The participating institutions seek to complement the conventional curriculum in systems science with one that admits computation as a primary concept. The curriculum changes will be aggressively promoted through a process of workshops and textbook preparation.

The objective of this research is to develop a prototype programmable microfluidic laboratory-on-chip that concurrently executes assays (chemical algorithms) in an on-line fashion. A chemist specifies an assay (chemical algorithm) using a text-based language. Assays arrive at the device in real-time and an operating system/virtual machine running on an attached microcontroller interprets them. The approach is to develop a software simulation infrastructure for the laboratory-on-chip and to build the operating system/virtual machine on top of it. The intellectual merit of this activity is due to the fact that no type of runtime support system has yet been proposed for microfluidic devices. The key challenges to be solved in this project include: deadlock-free deterministic and adaptive routing algorithms; real-time constraints for routing droplets in the system; routing wash droplets for decontamination; scheduling assay operations on the devices; congestion estimation; and fault diagnosis and recovery. In terms of broader impact, advances in laboratory-on-chip technology will improve public health worldwide and lead to significant advances in clinical diagnostics and medicine. Laboratory-on-chips are commercially available from established companies such as Agilent Technologies as well as startup companies such as Advanced Liquid Logic, Silicon Biosystems, and Ayanda Biosystems; thus, the economic impact of this research is tremendous. The University of California, Riverside is a Minority-Serving Institution. The PI is committed to the introduction of laboratory-on-chip technology in both undergraduate and graduate education and will make every possible effort to recruit underrepresented minorities (including women) at the graduate and undergraduate level to work on the project.

The objective of this research is to enable cyberphysical systems (CPS) to be context-aware of people in the environment and to use data from real-world probabilistic sensors. The approach is (1) to use radio tomography (RT) and RFID to provide awareness (location and potential identification) of every person in a building or area, and (2) to develop new middleware tools to enable context-aware computing systems to use probabilistic data, thus allowing new applications to exploit sometimes unreliable estimates of the environment.The intellectual merit of the proposal is in the development of new algorithms and models for building-scale RT with low radio densities and across multiple frequencies; the development of efficient multichannel access protocols for rapid and adaptive peer-to-peer measurements; the development of space-time and probabilistic data representations for use in stream-based context awareness systems and for merging ID and non-ID data; (4) and the development of a human context-aware software development toolkit that interfaces between probabilistic data and context-aware applications. The proposal impacts broadly the area of Cyber-physical systems that reason about human presence and rely on noisy and potentially ambiguous (practical) sensors. The research has additional dramatic impact in: (1) smart facilities which automatically enforce safety, privacy, and security procedures, increasing the ability to respond in emergency situations and prevent accidents and sabotage; (2) elder care, to monitor for physical or social decline so that effective intervention can be implemented, extending the period elders can live in their own home, without pervasive video surveillance.

Using the newly introduced idea of a sensor lattice, this project conducts a systematic study of the "granularity'' at which the world can be sensed and how that affects the ability to accomplish common tasks with cyber-physical systems (CPSs). A sensor is viewed as a device that partitions the physical world states into measurement-invariant equivalence classes, and the sensor lattice indicates how all sensors are related. Several distinctive characteristics of the pursued approach are: 1) Virtual sensor models are developed, which correspond to minimal information requirements of common tasks and are independent of particular physical sensor implementations. 2) Uncertainty is decoupled into disturbances and pre-images, the latter of which yields the measurement-invariant equivalence classes and sensor lattice. 3) The development of particular spatial and temporal filters that are based on minimal information requirements of a task. 4) Formally establishing the conditions that enable sensors in a CPS to be interchanged, and then determining the relative complexity tradeoffs. The intellectual merit is to understand how mappings from the physical world to sensor outputs affect the solvability and complexity of commonly occurring tasks. This is a critical step in the development of mathematical and computational CPS foundations. Broader impact is expected by improving design methodologies for CPS solutions to societal problems such as assisted living, environmental monitoring, and automated agriculture. The sensor lattice approach is transformative because it represents a new paradigm with which to address basic sensor-based inference issues, which extend well beyond the traditional academic boundaries.

Body Area Sensor Networks: A Holistic Approach from Silicon to Users The objective of this research is to develop new principles and techniques for adaptive operation in highly dynamic physical environments, using miniaturized, energy-constrained devices. The approach is to use holistic cross-layer solutions that simultaneously address all aspects of the system, from low-level hardware design to higher-level communication and data fusion algorithms to top-level applications. In particular, this work focuses on body area sensor networks as emerging cyber-physical systems. The intellectual merit includes producing new principles regarding how cyber systems must be designed in order to continually adapt and respond to rapidly changing physical environments, sensed data, and application contexts in an energy-efficient manner. New cross-layer technologies will be created that use a holistic bottom-up and top-down design -- from silicon to user and back again. A novel system-on-a-chip hardware platform will be designed and fabricated using three cutting-edge technologies to reduce the cost of communication and computation by several orders of magnitude. The broad impact of this project will enable the wide range of applications and societal benefits promised by body area networks, including improving the quality and reducing the costs of healthcare. The technology will have broad implications for any cyber physical system that uses energy constrained wireless devices. A new seminar series will bring together experts from many fields (including domain experts, such as physicians and healthcare professionals). The key aspects of this work that deal with healthcare have the potential to attract women and minorities to the computer field.

The objective of this research is to improve the ability to track the orbits of space debris and thereby reduce the frequency of collisions. The approach is based on two scientific advances: 1) optimizing the scheduling of data transmission from a future constellation of orbiting Cubesats to ground stations located worldwide, and 2) using satellite data to improve models of the ionosphere and thermosphere, which in turn are used to improve estimates of atmospheric density. Intellectual Merit Robust capacity-constrained scheduling depends on fundamental research on optimization algorithms for nonlinear problems involving both discrete and continuous variables. This objective depends on advances in optimization theory and computational techniques. Model refinement depends on adaptive control algorithms, and can lead to fundamental advances for automatic control systems. These contributions provide new ideas and techniques that are broadly applicable to diverse areas of science and engineering. Broader Impacts Improving the ability to predict the trajectories of space debris can render the space environment safer in both the near term---by enhancing astronaut safety and satellite reliability---and the long term---by suppressing cascading collisions that could have a devastating impact on the usage of space. This project will impact real-world practice by developing techniques that are applicable to large-scale modeling and data collection, from weather prediction to Homeland Security. The research results will impact education through graduate and undergraduate research as well as through interdisciplinary modules developed for courses in space science, satellite engineering, optimization, and data-based modeling taught across multiple disciplines.