CAREER: Information-Scaling Laws, ``Bit-conservation'' Principles, and Robust Coding Architectures in Sensor Networks

职业：传感器网络中的信息扩展定律、“位守恒”原则和鲁棒编码架构

• 批准号: 0546598
• 负责人: Prakash Ishwar
• 金额: --
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-12-15 至 2011-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0546598&HistoricalAwards=false
• 关键词: CAREER; Information; Scaling; Laws; Bit

With a vision for architecting the next generation video-based sensor networks capable of real-time ``superresolution imaging'' using a large distributed network of poor-resolution wireless cameras, thisproject introduces new paradigms for distributed sampling and video coding that lie in the frontier of signal processing and network information theory. The new data-acquisition, compression, and inference methods developed in this project are expected to influence the architecture and evolution of large-scale wireless sensor networks and advance the state-of-the-art in applications requiring active monitoring of telemetry data such as surveillance, homeland security, intelligent transportation, and environmental monitoring.This project 1) studies fundamental performance limits and constructive approaches for integrating poor device precision and large-scale deployment with distributed sampling and compression using new results in nonharmonic Fourier analysis, dithered sampling, and Wyner-Ziv coding and 2) develops new real-time distributed video-coding architectures that are amenable to flexible distribution of processing complexity and sensing resolution and are robust to information loss and correlation uncertainty. A novel ``bit-conservation'' principle is introduced for characterizing the tradeoffs between sensor precision and sensor density in distributed sampling. The research effort is complemented by an educational effort to train young engineers to become skilled in the design and development of distributed information systems through 1) curriculumdevelopment, with a new course on distributed information processing and communication having an emphasis on raw-research and project development, 2) the compilation of a corpus of striking toy researchpuzzles illustrating fundamental concepts in distributed signal processing and network information theory integrated into the undergraduate and graduate curricula, and 3) the creation of a new introductory graduate-level text-book on information theory in distributed signal processing.

与架构下一代基于视频的传感器网络能够实时“超分辨率成像”使用一个大型分布式网络的低分辨率无线摄像机的愿景，该项目介绍了新的范例分布式采样和视频编码，在信号处理和网络信息理论的前沿。该项目开发的新数据采集、压缩和推理方法有望影响大规模无线传感器网络的架构和发展，并在需要主动监测遥测数据的应用中推进最新技术，如监视、国土安全、智能交通、该项目1）研究基本性能限制和建设性方法，以整合不良设备精度和大型-使用非谐波傅立叶分析、抖动采样和Wyner-Ziv编码中的新结果，利用分布式采样和压缩进行规模部署，以及2）开发新的实时分布式视频编码架构，其适合于处理复杂度和感测分辨率的灵活分布，并且对信息丢失和相关不确定性是鲁棒的。介绍了一种新的“比特守恒”原理，用于表征分布式采样中传感器精度和传感器密度之间的权衡。研究工作得到了教育工作的补充，以培训年轻的工程师，使他们能够通过以下方式熟练地设计和开发分布式信息系统：1）分布式开发，新的分布式信息处理和通信课程强调原始研究和项目开发，（二）汇编了一个引人注目的玩具研究拼图语料库，说明了分布式信号处理和网络信息理论的基本概念，本科生和研究生课程，以及3）创建一个新的介绍研究生水平的教科书信息理论在分布式信号处理。