CSR---CSI: Adaptive end-to-end software infrastructure for sensor-based science

CSR---CSI：基于传感器的科学的自适应端到端软件基础设施

• 批准号: 0720730
• 负责人: Andreas Terzis
• 金额: $ 3万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0720730&HistoricalAwards=false
• 关键词: CSR; CSI; Adaptive; end; software

Wireless sensor networks (WSNs) are transforming many areas of modern science, from ecology, to civil engineering, and public health. At the same time, experiments with WSN testbeds have exposed a number of shortcomings of the current technologies that hamper the wider adoption of this technology by domain scientists. In particular, inexpensive sensor transducers used as sensors often fail intermittently in complex and unexpected ways. Moreover, given the small number of sensors, their hardware limitations, and the complexity of tracking unexpected phenomena, sensor networks may fail to accurately record punctuated events (e.g. flash floods and hailstorms). In this project we compare the effectiveness and efficiency of different statistical methods used to detect whether sensors are misbehaving. We investigate both off-line and on-line techniques that can be implemented on resource-limited sensor nodes to detect faults in real time. We also investigate the use of similar techniques for learning the inherent characteristics of the physical phenomena that the network is monitoring. This knowledge can be used to dynamically detect and report the onset of punctuated events and modify the behavior of the network accordingly. We will evaluate the performance of these algorithms using archived data and implement them on the nodes of a wireless sensor network used for soil monitoring. The outcome of this project will be a set of algorithms that can be broadly used to build responsive and efficient wireless sensor networks for sensor-based science.

无线传感器网络(WSN)正在改变现代科学的许多领域，从生态学到土木工程和公共卫生。与此同时，WSN试验台的实验暴露了当前技术的一些缺陷，这些缺陷阻碍了领域科学家更广泛地采用这项技术。特别是，用作传感器的廉价传感器传感器经常以复杂和意想不到的方式间歇性故障。此外，考虑到传感器数量较少、硬件限制以及跟踪意外现象的复杂性，传感器网络可能无法准确记录断断续续的事件(例如山洪暴发和冰雹)。在这个项目中，我们比较了不同的统计方法用于检测传感器是否行为不当的有效性和效率。我们研究了可以在资源有限的传感器节点上实现的离线和在线技术，以实时检测故障。我们还研究了如何使用类似的技术来了解网络监控的物理现象的固有特征。该知识可用于动态检测和报告间断事件的发生，并相应地修改网络的行为。我们将使用归档数据评估这些算法的性能，并在用于土壤监测的无线传感器网络的节点上实现它们。该项目的成果将是一套算法，可广泛用于为基于传感器的科学建立响应迅速且高效的无线传感器网络。