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

基本信息

项目摘要

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.
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。

项目成果

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Venugopal Veeravalli其他文献

Venugopal Veeravalli的其他文献

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{{ truncateString('Venugopal Veeravalli', 18)}}的其他基金

Collaborative Research: CIF: Medium: Emerging Directions in Robust Learning and Inference
协作研究:CIF:媒介:稳健学习和推理的新兴方向
  • 批准号:
    2106727
  • 财政年份:
    2021
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Continuing Grant
Efficient Strategies for Pandemic Monitoring and Recovery
流行病监测和恢复的有效策略
  • 批准号:
    2033900
  • 财政年份:
    2020
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant
SpecEES: Collaborative Research: Energy Efficient Dynamic Spectrum Access in Uncoordinated Networks
SpecEES:协作研究:不协调网络中的节能动态频谱接入
  • 批准号:
    1730882
  • 财政年份:
    2017
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant
CIF: Small: Collaborative Research: Network Event Detection with Multistream Observations
CIF:小型:协作研究:通过多流观察进行网络事件检测
  • 批准号:
    1618658
  • 财政年份:
    2016
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant
CIF: Medium: Collaborative Research: Quickest Change Detection Techniques with Signal Processing Applications
CIF:媒介:协作研究:信号处理应用的最快变化检测技术
  • 批准号:
    1514245
  • 财政年份:
    2015
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Continuing Grant
WiFiUS: Message and CSI Sharing for Cellular Interference Management with Backhaul Constraints
WiFiUS:用于具有回程约束的蜂窝干扰管理的消息和 CSI 共享
  • 批准号:
    1457168
  • 财政年份:
    2015
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant
IF: Student Travel Support for the 2014 IEEE International Symposium on Information Theory
IF:2014 年 IEEE 国际信息论研讨会学生旅行支持
  • 批准号:
    1434211
  • 财政年份:
    2014
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant
Collaborative Research: ATD: Advanced Quickest Multidecision Change Detection-Classification Methods for Threat Assessment in Distributed Sensing Systems
合作研究:ATD:分布式传感系统中威胁评估的先进最快多决策变化检测分类方法
  • 批准号:
    1222498
  • 财政年份:
    2012
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Continuing Grant
CIF:Medium:Collaborative Research: Understanding and Managing Interference in Communication Networks
CIF:中:协作研究:理解和管理通信网络中的干扰
  • 批准号:
    0904619
  • 财政年份:
    2009
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant
Collaborative Research: Optimal Changepoint Detection and Identification Algorithms with Applications
协作研究:最优变点检测和识别算法及其应用
  • 批准号:
    0830169
  • 财政年份:
    2008
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant

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    2007
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    29.0 万元
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相似海外基金

Collaborative Research: CIF: Small: New Theory, Algorithms and Applications for Large-Scale Bilevel Optimization
合作研究:CIF:小型:大规模双层优化的新理论、算法和应用
  • 批准号:
    2311274
  • 财政年份:
    2023
  • 资助金额:
    $ 106.93万
  • 项目类别:
    Standard Grant
Collaborative Research: CIF: Small: New Theory, Algorithms and Applications for Large-Scale Bilevel Optimization
合作研究:CIF:小型:大规模双层优化的新理论、算法和应用
  • 批准号:
    2311275
  • 财政年份:
    2023
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    $ 106.93万
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Collaborative Research: CIF: Small: Low-Complexity Algorithms for Unsourced Multiple Access and Compressed Sensing in Large Dimensions
合作研究:CIF:小型:大维度无源多址和压缩感知的低复杂度算法
  • 批准号:
    2131115
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    2021
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Collaborative Research: CIF: Small: Low-Complexity Algorithms for Unsourced Multiple Access and Compressed Sensing in Large Dimensions
合作研究:CIF:小型:大维度无源多址和压缩感知的低复杂度算法
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    2131106
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Collaborative Research: CIF: Small: Convexification-based Decomposition Methods for Large-Scale Inference in Graphical Models
合作研究:CIF:小型:图模型中大规模推理的基于凸化的分解方法
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    2006762
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Collaborative Research: CIF: Small: Convexification-based Decomposition Methods for Large-Scale Inference in Graphical Models
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    $ 106.93万
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CIF: Small: Collaborative Research: Acceleration Algorithms for Large-scale Nonconvex Optimization
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    1909291
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CIF: Small: Collaborative Research: Acceleration Algorithms for Large-scale Nonconvex Optimization
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