MavEstream: Synergistic Integration of Stream and Event Pocessing

IIS-0534611 Sharma Chakravarthy Sharma@cse.uta.edu德克萨斯大学ArlingtonMavEStream：流和事件处理的协同集成本研究项目的目标是促进流处理与事件处理的协同集成，以满足新型应用(例如，智能家居监控、高速公路上的事故监控)的需求。将流处理中的窗口概念推广并增强为既可应用于流又可应用于事件的语义窗口。在事件处理(使用调度和减负策略)的上下文中解决服务质量(Qos)要求，以获得无缝的端到端系统。对现有的基于时间的事件操作符语义进行了扩展，加入了基于属性的语义，提高了事件操作符的表现力。还讨论了在存在基于属性的语义的情况下事件操作符的优化。实现了一个结合本研究结果的原则性证明系统。使用线性道路基准和智能家居监控(例如MavHome)的数据进行了广泛的性能和可扩展性实验，以评估算法的有效性和系统的实现。这项研究的结果将对传感器以及普适计算应用产生深远的影响，如环境监测、基于RFID和GIS的跟踪和监测系统。它们将被整合到大学教师的研究生和本科课程中，并将通过论文和报告以及项目网站(http://itlab.uta.edu/sharma/projects/mavestream/index.htm).进行传播

IIS-0534611Sharma Chakravarthy sharma@cse.uta.eduThe University of Texas at ArlingtonMavEStream: Synergistic Integration of Stream and Event ProcessingThe goal of this research project is to facilitate a synergistic integration of stream processing with event processing to meet the needs of new class of applications (e.g., intelligent home monitoring, accident monitoring on highways). The concept of window in stream processing is generalized and enhanced to a semantic window that can be applied to both streams and events. Quality of service (QoS) requirements is addressed in the context of event processing (using scheduling and load shedding strategies) to obtain a seamless end-to-end system. Current time-based semantics of event operators is extended to include attribute-based semantics to increase the expressiveness of event operators. Optimization of event operators in the presence of attribute-based semantics is addressed as well. A proof-of-principle system to incorporate the results of this research is implemented. Extensive performance and scalability experiments are conducted using data from linear road benchmark and intelligent home monitoring (e.g., MavHome) to evaluate the effectiveness of the algorithms and the implementation of the system. The results of this research will have far reaching effects on sensor as well as pervasive computing applications such as environmental monitoring, RFID- and GIS-based tracking and monitoring systems. They will be integrated into graduate and undergraduate courses taught at UTA, and will be disseminated through papers and reports and via the project Web site (http://itlab.uta.edu/sharma/projects/mavestream/index.htm).