DocumentCode :
2117958
Title :
RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System
Author :
Hogenboom, A. ; Niewenhuijse, E. ; Hogenboom, Frederik ; Frasincar, Flavius
Author_Institution :
Erasmus Univ. Rotterdam, Rotterdam, Netherlands
Volume :
1
fYear :
2012
fDate :
4-7 Dec. 2012
Firstpage :
74
Lastpage :
81
Abstract :
In order to effectively and efficiently disclose the ever-growing amount of widely distributed RDF data to demanding users in real-time environments, RDF query engines need to optimize the join order of partial query results. For this, a two-phase optimization (2PO) algorithm and a genetic algorithm (GA) have already been proposed. We propose an alternative approach - an ant colony system (ACS). On a large RDF data source, our approach significantly outperforms both 2PO and the GA in terms of execution time and solution quality for RDF chain queries consisting of up to about ten joins. For larger queries, our novel ACS delivers solutions of better quality than 2PO does, while realizing a solution quality that is comparable to the solution quality of the GA method. However, the GA approach offers the best trade-off between execution time and solution quality for such larger queries.
Keywords :
ant colony optimisation; query processing; ACS; RCQ-ACS framework; RDF chain query engine optimization; Resource Description Framework; ant colony system; distributed RDF data; execution time; partial-query; solution quality; RDF chain query optimization; ant colony system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
Conference_Location :
Macau
Print_ISBN :
978-1-4673-6057-9
Type :
conf
DOI :
10.1109/WI-IAT.2012.63
Filename :
6511868
Link To Document :
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