CIF: Large: Collaborative Research: Controlled Sensing, and Distributed Signal Processing and Decision Making in Networked Systems

到岸价：大号：合作研究：受控传感，分布式信号处理和决策网络系统PI：Demosthenis Teneketzis（密歇根州）和Venugopal Veeravalli（伊利诺伊州）摘要：许多现代技术系统是网络系统。网络化系统是信息分散的，包括许多携带不同信息的节点，并且受到能量、数据存储和计算能力的约束。该研究项目需要对网络系统中出现的基本问题进行全面研究，这些问题涉及受控传感，分布式信号处理和分布式决策，其解决方案将导致网络性能的大幅改善。该项目的目的是：（一）提高我们对信息在各种体系结构下，在受控和分布式环境中的网络系统的传感，信号处理和决策中的作用的理解;（二）通过评估不同体系结构的性能，提高我们对网络系统协调的理解;以及（iii）产生新颖的算法，其将导致表现出优于当前系统的上级性能的联网系统。这些目标背后的问题不能充分利用信号处理或随机和确定性控制理论的标准方法来解决。研究人员使用随机优化，分布式计算和概率论的关键工具来开发解决潜在挑战的新方法。该项目在几个方面具有更广泛的影响。它提供了系统的设计方法，在许多现代网络系统中是必不可少的，特别是在环境（例如，土壤湿度）监测与分布式传感器。此外，该项目的研究成果有望对NSF的氖计划、NASA的地球科学计划和NOAA的监测计划有所帮助。研究活动预计将通过课程开发和学生培训对技术转让和研究生教育产生影响，特别强调通过强有力的导师计划将妇女和代表性不足的少数民族学生包括在内。

CIF: Large: Collaborative Research: Controlled Sensing, and Distributed Signal Processing and Decision Making in Networked Systems PIs: Demosthenis Teneketzis (Michigan) and Venugopal Veeravalli (Illinois) Abstract: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.