R-SOX: runtime semantic query optimization over XML streams

Authors:
Song Wang;Hong Su;Ming Li;Mingzhu Wei;Shoushen Yang;Drew Ditto;Elke A. Rundensteiner;Murali Mani
Affiliations:
Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA;Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA;Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA;Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA;Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA;Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA;Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA;Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA
Venue:
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Year:
2006

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Abstract

Optimizing queries over XML streams has been an important and non-trivial issue with the emergence of complex XML stream applications such as monitoring sensor networks and online transaction processing. Our system, R-SOX, provides a platform for runtime query optimization based on dynamic schema knowledge embedded in the XML streams. Such information provides refined runtime schema knowledge thus dramatically enlarged the opportunity for schema-based query optimizations. In this demonstration, we focus on the following three aspects: (1) annotation of runtime schema knowledge; (2) incremental maintenance of run-time schema knowledge; (3) dynamic semantic query optimization techniques. The overall framework for runtime semantic query optimization, including several classes of dynamic optimization techniques, will be shown in this demonstration.