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

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 proceeding › Conference contribution

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 language	English (US)
Title of host publication	VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases
Publisher	Association for Computing Machinery
Pages	1207-1210
Number of pages	4
ISBN (Print)	1595933859, 9781595933850
State	Published - 2006
Externally published	Yes
Event	32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of Duration: Sep 12 2006 → Sep 15 2006

Publication series

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

Conference

Conference	32nd International Conference on Very Large Data Bases, VLDB 2006
Country/Territory	Korea, Republic of
City	Seoul
Period	9/12/06 → 9/15/06

ASJC Scopus subject areas

Hardware and Architecture
Information Systems
Software
Information Systems and Management

Cite this

Wang, S., Su, H., Li, M., Wei, M., Yang, S., Ditto, D., Rundensteiner, E. A., & Mani, M. (2006). R-SOX: Runtime Semantic Query Optimization over XML Streams. In VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases (pp. 1207-1210). (VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases). Association for Computing Machinery.

R-SOX: Runtime Semantic Query Optimization over XML Streams. / Wang, Song; Su, Hong; Li, Ming et al.
VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases. Association for Computing Machinery, 2006. p. 1207-1210 (VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wang, S, Su, H, Li, M, Wei, M, Yang, S, Ditto, D, Rundensteiner, EA & Mani, M 2006, R-SOX: Runtime Semantic Query Optimization over XML Streams. in VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases. VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases, Association for Computing Machinery, pp. 1207-1210, 32nd International Conference on Very Large Data Bases, VLDB 2006, Seoul, Korea, Republic of, 9/12/06.

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title = "R-SOX: Runtime Semantic Query Optimization over XML Streams",

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.",

author = "Song Wang and Hong Su and Ming Li and Mingzhu Wei and Shoushen Yang and Drew Ditto and Rundensteiner, \{Elke A.\} and Murali Mani",

note = "Funding Information: Our thanks to NSF for the support on grants IIS 0414567 and CNS 0551584. Publisher Copyright: Copyright 2006 VLDB Endowment, ACM; 32nd International Conference on Very Large Data Bases, VLDB 2006 ; Conference date: 12-09-2006 Through 15-09-2006",

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R-SOX: Runtime Semantic Query Optimization over XML Streams

Abstract

Publication series

Conference

ASJC Scopus subject areas

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