Method of Complex Event Processing over XML Streams

This paper describes a query processing engine for multiple continuous XML data streams with correlated data as a notification mechanism for navigating data exploration. Stream processing, including formal models for stream filtering, union, activation, decomposition, and partition, is formulated in algebraic expressions. In addition, a query language, called QLMXS, over XML streams for complex event processing is described. QLMXS supports all functions of the algebraic expressions in a SQL-like form. QLMXS queries are converted into a visibly pushdown automaton (VPA) that analyzes complex event data from the XML streams. The VPA engine concurrently processes multiple XML data on multiple levels; therefore, it is very important to tune the performance of the engine. Four optimization methods are proposed to improve performance by utilizing VPA and XML features: VPA-state reduction, VPA unification, delayed evaluation, and elimination of unnecessary XML processing. Experimental results demonstrate that VPA unification increases the processing speed of the VPA engine 1.6 times, and the overall processing speed is increased 2.6 times.