An XML Framework for Integrating Continuous Queries, Composite Event Detection, and Database Condition Monitoring for Multiple D

Abstract Current, data-driven applications have become more dynamic in nature, with the need to respond to events generated from distributed sources or to react to information extracted from incoming data streams. Event processing and stream processing have traditionally developed as two separate areas of research. Event processing has its roots in research with active rule processing (Widom and Ceri, 1996) as well as distributed systems (Muhl et al., 2006), with a focus on composite event specification languages and execution issues for detecting, broadcasting, and consuming streams of events. More recently, data stream processing has developed as a new form of data management, with a focus on the continuous execution of queries over data generated from sensors or other sources that emit streams of data that must be quickly analyzed (Golab and Ozsu, 2003; Arasu et al., 2003). Research on data streams mainly focuses on continuous (and potentially infinite) sequences of data, investigat...

• Type: Conference
• Year: 2007
• Where: DAGSTUHL
• Authors: Susan Darling Urban, Suzanne W. Dietrich, Yi Chen
• Keywords: DAGSTUHL 2007, Data Streams, Event Processing, Software Engineering, Stream Processing