Algorithms and Metrics for New Generation Data Stream Management Systems

IIS-0534531 Panos K.Chrysanthis Panos@cs.bitt.edu匹兹堡大学新一代数据流管理系统的算法和指标本项目的目标是设计新一代数据流管理系统(DSSMS)，同时优化性能和增强功能。新一代DMS简化了具有不同需求的各种监控应用程序的开发。监测应用程序是科学探索、健康警报、环境监测和业务支持系统的核心组件。本项目重新研究了DSM的所有四个关键组件：查询调度器、减载器、查询处理器和数据分发模块。该项目的两个关键创新是：(1)它着眼于如何将这四个模块集成在一起工作，而不是单独做出对整体性能有重大影响的决策；(2)该项目正式确定了DMS的QOS/QOD指标，并开发了旨在优化这些指标的算法。此外，项目计划还包括对所提出的算法进行分析和实验评估，以及原型系统的实现和评估。该项目为研究生和本科生提供了参与尖端技术发展的机会。这项研究的结果，包括软件、数据和出版物，将通过项目网站http://db.cs.pitt.edu/streams发布

IIS-0534531Panos K. Chrysanthis panos@cs.pitt.eduUniversity of PittsburghAlgorithms and Metrics for New Generation Data Stream Management SystemsThe goal of this project is to design a new generation of data stream management systems (DSMSs), with equal emphasis on optimizing performance and enhancing functionality. New generation DSMSs simplify the development of a wide range of monitoring applications, with diverse requirements. Monitoring applications are core components in scientific exploration, health alerting, environmental monitoring, and business support systems. This project reexamines all four critical components of a DSMS: query scheduler, load shedder, query processor, and data dissemination modules. The two key innovations of this project are: (1) it looks at how these four modules can be integrated to work in combination, instead of making in isolation decisions that have a significant impact on the overall performance; and (2) this project formalizes QoS/QoD metrics for DSMSsand develops algorithms designed to optimize these metrics. In addition, the project plans include the analytical and experimental evaluation of the proposed algorithms and also the implementation and evaluation of a prototype system. This project provides opportunities for both graduate and undergraduate students to participate in the development of cutting edge technology. Results of this research, including software, data, and publications, will be disseminated via the project Web site at http://db.cs.pitt.edu/streams