NeTS: Small: Collaborative Research: Compressed Network Tomography and Data Collection in Large-Scale Wireless Sensor Networking

我们的物理世界呈现出一套极其丰富的观察模式。无线传感器网络（WSNs）的最新进展使人们能够以前所未有的高空间密度和长时间持续监测各种物理现象，从而为许多科学努力开辟了令人兴奋的新机会。由于传感器节点无人值守且由电池供电，因此从接收器处间接测量的网络监测/断层扫描和节能对于大规模环境wsn的部署至关重要。因此，一个可行的节能网络监控和数据收集框架对于显著改善WSN的管理/运营并降低其部署成本至关重要。本项目基于压缩感知（CS）的最新突破，通过理论和实证相结合的方法，研究了大规模户外wsn的节能网络监测/断层扫描和数据收集。本课题研究无线网络拓扑层析成像在信道衰落和干扰下的动态路由问题。该项目的目标是为在高噪声通信环境中运行的真实wsn开发一种新颖而严格的拓扑层析成像框架。动态路由拓扑恢复算法设计为完全间接测量和不完全间接测量接收到的汇(s)。从分析和经验两方面研究了层析成像方法的准确性。所开发的WSN拓扑层析成像框架不仅在实践中对WSN的路由改进、拓扑控制、热点消除和异常检测至关重要，而且对于新兴的基于cs的数据采集也至关重要。该方法扩展了现有的CS技术，形成了大规模WSN网络层析成像和数据采集的统一框架，并在此基础上开发了节能的WSN拓扑层析成像和数据采集协议组。开发的框架和协议套件将在丘陵流域的真实环境WSN测试台上进行验证和评估。该项目旨在为大规模无线传感器网络创建优化设计、开发和管理/运营的新范例，以显着延长其使用寿命。这将导致在不久的将来为科学、民用、国家安全和军事目的大规模部署WSN的成本大幅降低。该项目通过实际WSN测试平台的实践经验，为本科生和研究生创造了一个跨学科的教育实践。推广活动包括为使用无线传感器网络试验台的学生举办夏令营和科学项目。

Our physical world presents an incredibly rich set of observation modalities. Recent advances in wireless sensor networks (WSNs) enable the continuous monitoring of various physical phenomena at unprecedented high spatial densities and long time durations, hence opening exciting new opportunities for numerous scientific endeavors. Since sensor nodes are unattended and batterypowered, network monitoring/tomography from indirect measurements at the sink(s) and energy conservation are critical in the deployment of large-scale environmental WSNs. Therefore, a viable framework for energy-efficient network monitoring and data collection is fundamentally important to significantly improve WSN management/operations and reduce its deployment costs.This project investigates the energy-efficient network monitoring/tomography and data collections in large-scale outdoor WSNs, based on the recent breakthrough of compressed sensing (CS) through an integrated theoretical and empirical approach. The project studies WSN topology tomography for dynamic routing under wireless link dynamics due to channel fading and interference. The objectives of this project are to develop a novel and rigorous framework of topology tomography for real-world WSNs operated in highly noisy communication environments. Dynamic routing topology recovery algorithms are devised for both complete indirect measurements and incomplete indirect measurements received at the sink(s). The accuracy of the tomography approach is studied both analytically and empirically. The developed WSN topology tomography framework can be essential not only for WSN's routing improvement, topology control, hot spot elimination, and anomaly detection in practice, but also for emerging CS-based data collection. This approach extends the current CS technology to form a unified framework for network tomography and data collection in large-scale WSNs, upon which energy-efficient WSN topology tomography and data gathering protocol suite is developed. The developed framework and protocol suite will be validated and evaluated in a real-world environmental WSN testbed in a hilly watershed.The project intends to create a new paradigm of optimal design, development, and management/operations for large-scale WSNs to significantly extend their lifetime. This would lead to a substantial reduction of the prohibitive cost of large-scale WSN deployments for scientific, civic, national security, and military purposes in the near future. The project creates an interdisciplinary educational practice for both undergraduate and graduate students through hands-on experience with a real-world WSN testbed. The outreach includes summer camps and scientific projects for school students using the WSN testbed.