NeTS-FIND: Sensor-Internet Sharing and Search
NeTS-FIND: Sensor-Internet Sharing and Search
批准号:
0626702
负责人:
John Heidemann
金额:
$0.0万
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
项目状态:
已结题
起止时间:
2006-10-01 至 2010-09-30
中文摘要
今天的传感器网络是许多无线孤岛,每一个都是孤立的,并通过互联网与其所有者相连,不容易被其他人使用。net - find:传感器-互联网共享和搜索(SISS)的目标是让业主能够轻松地连接这些传感器孤岛,与互联网上的任何人共享他们的数据,并帮助客人发现和探索这些共享的传感器数据。因此,本研究寻求融合不断发展的传感器和互联网架构,采用新的方法:b.允许将新的传感器轻松集成到互联网和通过互联网桥接的传感器集成;管理传感器数据的披露,支持机密性、数据质量估计和趋势可视化;支持传感器发现、链接和搜索。这项工作的结果预计将包括共享传感器数据流的新协议,用于在互联网上存档传感器数据,并允许用户搜索、聚合和处理这些数据流。pi将通过设计新算法,通过仿真和原型实现对其进行评估来探索这项研究。pi期望指定支持这项工作的协议和元素,以便将来对单个组件进行优化。除了这项研究的直接影响,这项研究的目标是使“公民科学家”,允许业余爱好者贡献传感器数据和处理传感器流。
英文摘要
Sensor networks today are many wireless islands, each isolated and connected through the Internet to its owner, not easily usable by others. The goal of NeTS-FIND: Sensor-Internet Sharing and Search (SISS) is to allow owners to easily bridge these sensornet islands, sharing their data with anyone on the Internet, and to help guests discover and explore these shared sensor data. This research therefore seeks to meld evolving sensornet and Internet architectures, with new approaches to:a. allow easy integration of new sensornets into the Internet and integration of sensornets bridged by the Internet;b. manage disclosure of sensor data, supporting confidentiality, estimates of data quality, and visualization of trends;c. support sensor discovery, linking and search.The results of this work are expected to include new protocols for sharing sensor data streams, for archiving sensor data on the Internet, and for letting users search, aggregate, and process these streams. The PIs will explore this research by designing new algorithms, evaluating them through simulation and prototype implementation. The PIs expect to specify the protocols and elements that enable this work, enabling future optimization of individual components.Beyond the immediate impact of this research, the goal of this research is to enable the "citizen scientist", allowing amateurs to contribute sensor data and process sensor streams.
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