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

CIF：大型：协作研究：网络系统中的受控传感、分布式信号处理和决策PI：Demosthenis Teneketzis(密歇根)和Venugopal Veeravalli(伊利诺伊州)摘要：许多现代技术系统都是网络系统。网络系统是信息分散的，由许多携带不同信息的节点组成，并且受到能量、数据存储和计算能力的限制。这项研究项目需要对网络系统中出现的基本问题进行全面的研究，这些问题涉及受控感知、分布式信号处理和分布式决策，这些问题的解决将导致网络性能的显著改善。该项目的目的是：(I)提高我们对信息在不同体系结构下、在受控和分布式环境下的网络化系统的感知、信号处理和决策中的作用的理解；(Ii)通过评估不同体系结构的性能，提高我们对网络化系统协调的理解；以及(Iii)产生新的算法，这些算法将导致联网系统表现出优于现有系统的性能。这些目标背后的问题不能用信号处理中的标准方法或随机和确定性控制理论来充分解决。研究人员使用来自随机优化、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。这个项目在几个方面都有更广泛的影响。它提供了在许多现代联网系统中必不可少的系统设计方法，特别是在具有分布式传感器的环境(例如土壤湿度)监测系统中。此外，该项目的研究成果预计将对NSF的霓虹灯计划、NASA的地球科学计划和NOAA的监测计划有用。预计研究活动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辅导方案吸纳妇女和代表性不足的少数族裔学生。

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.