ITR: Real-Time Data Aware System for Earth, Oceanographic, and Environmental Applications

该项目的研究重点是动态适应下游处理和建模，因为传感器被添加到实时数据网络或从实时数据网络中删除。 该研究还将包括自动检测实时数据流中有趣现象发生的方法，以及触发数据分析，建模计算或打开或关闭传感器网络部分等响应的方法。 这种能力一旦得到发展，将可能有助于氖、地球镜、NEES和ORION等大型环境观测项目。 该项目建立在HPWREN项目下开发的无线网络基础设施、ROADNet项目下开发的数据管理方法以及关于“数据网格”的现有想法（如在BIRN和GEON项目下开发和测试的想法）的基础上。 后一种数据网格技术是围绕在数据存储到数据库中之后查找和操作数据的概念构建的。 该项目将研究如何扩展数据网格的概念，以包括实时数据流，并允许观测和观测网络的操作之间的反馈。所涉及的任务包括开发分布式数据处理系统所需的数据缓存结构和数据流管理，用于不同带宽的多个实时数据流，开发一种能够在分层和多学科元数据结构中进行搜索的信息发现系统，从实时信息流中提取元数据，以及集成异步，在数据传输系统的不同阶段的自主处理能力。 该工作包括将现有的ORB和SRB技术合并为一个虚拟对象环形缓冲区（VORB）和虚拟元数据目录体系结构，用于实时数据。 VORB的计划设计还包括增加数据推送功能。 该项目将产生一个工作原型，数据来自各种不同的传感器网络，包括虚拟地震网络、约塞米蒂国家公园和圣玛格丽塔河流域的水文和气象观测、圣地亚哥海岸监测和观测系统和南加州海岸海洋观测系统、橙子县和西部滨江县的全球定位系统/地震系统，该项目有可能对环境研究的若干领域产生影响。 这种能力一旦得到发展，将可能对大规模环境观测项目有用，如氖、Earthscope、NEES、ORION、LTER网络、环境工程实地设施和水文观测网络。 成功地开发和展示一种技术，以综合和管理来自各种观测系统的存档和实时数据，也可以为综合获取从各种联邦和州机构支持的观测系统收集的环境数据提供一个共同框架。

The research in this project will focus on dynamically adapting downstream processing and modeling as sensors are added to or removed from a real-time data network. The research will also include work on methods to detect automatically the occurrence of interesting phenomena in real-time data streams and to trigger responses such as data analysis, modeling computations or turning on or off parts of the sensor network. Once developed, this type of capability will be potentially useful to large-scale environmental observing projects such as NEON, Earthscope, NEES and ORION. The project builds on the wireless networking infrastructure developed under the HPWREN project, the data management approach developed under the ROADNet project, and existing ideas about "data grids" such as those being developed and tested under the BIRN and GEON projects. The latter data grid technology is built around the concept of finding and manipulating data after it is stored in databases. The proposed project will investigate how to extend data grid ideas to include real-time data streams and permit feedback between observations and the operation of the observing network.Tasks involved including developing the data cache structure and data flow management needed for a distributed data-handling system for multiple real-time data streams of varying bandwidth, the development of an information discovery system capable of searching across a hierarchical and multi-disciplinary metadata structure, the extraction of metadata from real-time information flows, and the integration of asynchronous, autonomous processing capability at different stages of the data transport system. The work includes merging the existing ORB and SRB technology into a virtual object ring buffer (VORB) and virtual metadata catalogue architecture for real-time data. The planned design for the VORBs also includes the addition of data-push features. The project will produce a working prototype, with data flowing from a variety of different sensor networks including the Virtual Seismic Network, hydrological and meteorological observations from Yosemite National Park and the Santa Margarita River basin, the San Diego Coastal Monitoring and Observing System and the Southern California Coastal Ocean Observing System, a GPS/seismic system for Orange and Western Riverside Counties, and SDSU field stations.The project has the potential for impacts in several areas of environmental research. Once developed, this type of capability will be potentially useful to large-scale environmental observing projects such as NEON, Earthscope, NEES, ORION, the LTER network, environmental engineering field facilities, and hydrologic observing networks. The successful development and demonstration of a technology to integrate and manage archived and real-time data coming from a diverse collection of observing systems could also provide a common framework for integrated access to environmental data collected from observing systems supported by a diverse collection of federal and state agencies.