CSR: Small: Collaborative Research: Systematic Approaches for Real-Time Stream Data Services

CSR：小型：协作研究：实时流数据服务的系统方法

• 批准号: 1117352
• 负责人: Kyoung-Don Kang
• 金额: $ 24.99万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1117352&HistoricalAwards=false
• 关键词: CSR; Small; Collaborative; Research; Systematic

Data-intensive real-time applications, such as transportation management, military surveillance, and network monitoring, need to handle massive amounts of stream data in a timely fashion. It is challenging to support real-time stream data services (RTSDS) due to stringent timing constraints, potentially unbounded continuous stream data, bursty stream data arrivals, and workload variations due to data value changes. This project will develop cost-effective methods and a runtime system for RTSDS. The project will systematically investigate methods and tools to support real-time continuous queries for RTSDS even in the presence of dynamic workloads. Specifically, the project will study a) real-time continuous query modeling, b) new performance metric design c) adaptive query scheduling design, d) tardiness control and load shedding, for both single node and clustered RTSDS. The project will also have prototype implementation and testbed evaluations. The results and findings of this project will advance and seamlessly integrate real-time computing and stream data management.Real-time stream data services (RTSDS) play an important role in many emerging application including intelligent transportation, green buildings, smart grid management, military surveillance, and network monitoring. Our everyday lives are highly dependent on these applications. RTSDS is a fundamental technology for developing critical data-intensive real-time applications with great socio-economic impacts. The project will develop the scientific foundations and associated engineering principles for building RTSDS. The project will provide excellent opportunities for undergraduate and graduate students to acquire hands-on experience as well as theoretical backgrounds in RTSDS. The PIs will work closely with students to carry out the research in this project. Through this project, the PIs will train students to become strong in both analytical and implementation skills, and help them solve challenging problems in RTSDS.

交通管理、军事监控、网络监控等数据密集型实时应用需要及时处理海量流数据。由于严格的时序限制、潜在的无限连续流数据、突发流数据到达以及数据值变化导致的工作负载变化，支持实时流数据服务 (RTSDS) 具有挑战性。该项目将为 RTSDS 开发具有成本效益的方法和运行时系统。该项目将系统地研究方法和工具，以支持 RTSDS 的实时连续查询，即使在存在动态工作负载的情况下也是如此。具体来说，该项目将研究单节点和集群 RTSDS 的 a) 实时连续查询建模，b) 新的性能指标设计，c) 自适应查询调度设计，d) 延迟控制和负载卸载。该项目还将进行原型实施和测试台评估。该项目的成果和发现将推进实时计算和流数据管理的无缝集成。实时流数据服务（RTSDS）在智能交通、绿色建筑、智能电网管理、军事等许多新兴应用中发挥着重要作用。监控、网络监控。我们的日常生活高度依赖这些应用程序。 RTSDS 是开发具有重大社会经济影响的关键数据密集型实时应用程序的基础技术。该项目将为构建 RTSDS 奠定科学基础和相关工程原理。该项目将为本科生和研究生提供获得 RTSDS 实践经验和理论背景的绝佳机会。 PI 将与学生密切合作开展该项目的研究。通过这个项目，PI 将培养学生增强分析和实施技能，并帮助他们解决 RTSDS 中的挑战性问题。