R-SOX: Runtime Semantic Query Optimization over XML Streams

Song Wang, Hong Su, Ming Li, Mingzhu Wei, Shoushen Yang, Drew Ditto, Elke A. Rundensteiner, Murali Mani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

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 runtime 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.

Original languageEnglish (US)
Title of host publicationVLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases
PublisherAssociation for Computing Machinery
Pages1207-1210
Number of pages4
ISBN (Print)1595933859, 9781595933850
StatePublished - 2006
Externally publishedYes
Event32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of
Duration: Sep 12 2006Sep 15 2006

Publication series

NameVLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases

Conference

Conference32nd International Conference on Very Large Data Bases, VLDB 2006
Country/TerritoryKorea, Republic of
CitySeoul
Period9/12/069/15/06

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems
  • Software
  • Information Systems and Management

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