NeTS-NOSS: Collaborative Research: Lightweight Monitoring Tools for Sensor Networks

NeTS-NOSS：协作研究：传感器网络的轻量级监控工具

• 批准号: 0627155
• 负责人: Ramesh Govindan
• 金额: $ 19万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0627155&HistoricalAwards=false
• 关键词: NeTS; NOSS; Collaborative; Research; Lightweight

Proposal Number: Collaborative Research: 0626954, 0626151, and 0627155PI: Ramesh Govindan, Leonidas Guibas, Subhash SuriInstitution: USC, Stanford, UCSBTitle: NeTS-NOSS: Lightweight Monitoring Tools for Sensor NetworksAbstract:Networks of tiny and inexpensive smart sensors have ushered a new generation of low-cost, large-scale, high-resolution, real-time sensing and actuation. As their economic importance grows along with their size and complexity, it becomes critical to ensure their operational health and robustness through continuous monitoring. With that motivation, this project develops lightweight monitoring algorithms and tools for sensor networks that allow the network operators to observe the large-scale behavior of the network and detect significant anomalies in network attributes or performance. The tools themselves are generic and can be composed to provide tailored solutions to meet various application-specific needs.The design of these monitoring tools requires inferring global aspects of the network through local information available at individual nodes. In order to synthesize a global summary from local views in a lightweight, energy-efficient manner, the project employs three methods: (1) intelligent sampling, (2) information aggregation, and (3) sparse representation of the signal landscape. These methods utilize mathematical techniques from geometry, topology, statistics, and distributed signal processing.The network monitoring tools enable better designed, more robust, trustworthy, and longer-lived sensor networks in operation. That, in turn lowers costs and enlarges the community of users as well as the set of potential commercial applications for networked sensing.The research output of this project includes novel algorithms, software tools, and their empirical evaluation using testbeds.

提案编号：合作研究：0626954，0626151，and 0627155 PI：Ramesh Govindan，Leonidas Guibas，Subhash Suri机构：USC，斯坦福大学，UCSB标题：NetS-NOSS：Lightweight Monitoring Tools for Sensor Networks摘要：由微型和廉价的智能传感器组成的网络已经迎来了新一代低成本、大规模、高分辨率、实时的传感和驱动。随着其经济重要性随着其规模和复杂性的沿着增长，通过持续监控确保其运营健康和稳健性变得至关重要。基于这一动机，该项目开发了用于传感器网络的轻量级监控算法和工具，使网络运营商能够观察网络的大规模行为，并检测网络属性或性能中的显著异常。这些工具本身是通用的，可以组成，以提供定制的解决方案，以满足各种应用程序的特定需求。这些监测工具的设计需要推断全球网络的各个方面，通过在各个节点的本地信息。为了以轻量级、节能的方式从局部视图合成全局摘要，该项目采用了三种方法：（1）智能采样，（2）信息聚合，以及（3）信号景观的稀疏表示。这些方法利用了几何学、拓扑学、统计学和分布式信号处理等数学技术，使传感器网络设计得更好、更健壮、更可靠、寿命更长。这反过来又降低了成本，扩大了用户社区以及网络传感的潜在商业应用。该项目的研究成果包括新颖的算法，软件工具，以及使用测试平台进行的经验评估。