NeTS-NOSS: Adaptivity in Sensor Networks for Optimized Distributed Sensing and Signal Processing

NeTS-NOSS：传感器网络的自适应性，用于优化分布式传感和信号处理

• 批准号: 0520280
• 负责人: Richard Baraniuk
• 金额: --
• 依托单位: William Marsh Rice 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: 2005-08-01 至 2011-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0520280&HistoricalAwards=false
• 关键词: NeTS; NOSS; Adaptivity; Sensor; Networks

This project aims to develop an adaptive sensor network architecture that enables the efficient, large-scale, long-term, low-cost, on-demand monitoring of a variety of physical phenomena with high fidelity. The core theme is that distributed signal processing and data assimilation of sensor data, as well as network management and monitoring, should be performed inside the sensor network in order to reduce energy consumption and global communication needs, leading to dramatically increased sensor lifetimes and much higher fidelity in the tracking of the physical phenomena of interest. The goal is to develop a flexible, self-monitoring architecture for this type of in-network processing and sensor networking that exploits adaptivity to significantly improve the network's efficiency, robustness, and usefulness. Two kinds of adaptivity are considered: (1) data adaptivity, where the network topology is adapted to align communications with the natural data flows; and (2) resource adaptivity, where the network topology is adapted based on computational, battery, or bandwidth resources. The expected results include the development of adaptive communication protocols and routing topology, the development of network management tools for sensor communication performance monitoring and inference, and for sensor distribution monitoring, as well as the experimental deployment of the adaptive sensor network architecture in a small-scale testbed of sensor nodes on the Rice University campus. Results will be disseminated through technical reports posted on the project web page, through papers presented at professional meetings, as well as through journal publications.

该项目旨在开发一种自适应传感器网络架构，能够高效、大规模、长期、低成本、按需监测各种高保真物理现象。核心主题是传感器数据的分布式信号处理和数据同化，以及网络管理和监控，应该在传感器网络内部进行，以减少能源消耗和全球通信需求，从而显着增加传感器寿命，并在跟踪感兴趣的物理现象时具有更高的保真度。我们的目标是为这种类型的网络内处理和传感器网络开发一种灵活的、自我监控的体系结构，利用自适应性来显著提高网络的效率、鲁棒性和实用性。考虑了两种自适应性：(1)数据自适应性，其中网络拓扑调整以使通信与自然数据流保持一致；(2)资源适应性，即网络拓扑根据计算资源、电池资源或带宽资源进行调整。预期结果包括自适应通信协议和路由拓扑的开发，用于传感器通信性能监控和推理以及传感器分布监控的网络管理工具的开发，以及自适应传感器网络架构在莱斯大学校园传感器节点的小型测试平台上的实验性部署。结果将通过在项目网页上登载的技术报告、在专业会议上提出的论文以及通过期刊出版物来传播。