Many modern technological systems are networked systems. Networked systems are informationally decentralized, comprise many nodes carrying disparate information, and are subject to constraints on energy, data storage and computational capabilities. This research project entails a comprehensive study of fundamental issues that arise in networked systems, pertaining to controlled sensing, distributed signal processing, and distributed decision making, whose resolution will lead to substantial improvements in network performance. The project aims at (i) improving our understanding of the role of information in sensing, signal processing and decision making for networked systems under various architectures, in controlled and distributed settings; (ii) improving our understanding of coordination of networked systems, by evaluating the performance of the different architectures; and (iii) generating novel algorithms that will lead to networked systems that exhibit superior performance over current ones. The problems underlying these objectives cannot be adequately tackled using standard approaches in signal processing or stochastic and deterministic control theory. The investigators use key tools from stochastic optimization, distributed computation, and probability theory to develop novel methodologies that address the underlying challenges.
This project has broader impact on several fronts. It provides systematic design methodologies that are essential in many modern networked systems, and in particular, in systems for environmental (e.g., soil moisture) monitoring with distributed sensors. In addition, the research output of this project is expected to be useful to NSF's NEON program, to NASA's earth science program, and to NOAA's monitoring program. The research activities are expected to have an impact on technology transfer and graduate education through course development and training of students, with a special emphasis on including women and under-represented minority students through a strong mentorship program.