RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System

Alexander Hogenboom; E Niewenhuijse; Frederik Hogenboom; Flavius Frasincar

doi:10.1109/WI-IAT.2012.63

RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System

Alexander Hogenboom, E Niewenhuijse, Frederik Hogenboom, Flavius Frasincar

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

3 Citations (Scopus)

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.

Original language	English
Title of host publication	2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012)
Editors	Z. Gong, Y.-M. Cheung, P. Lingras, N. Zhong, P.S. Szczepaniak, E. Suzuki
Publisher	IEEE Computer Society
Pages	74-81
Number of pages	8
DOIs	https://doi.org/10.1109/WI-IAT.2012.63
Publication status	Published - 4 Dec 2012

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EUR ESE 32

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10.1109/WI-IAT.2012.63

http://hdl.handle.net/1765/40598

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Hogenboom, A., Niewenhuijse, E., Hogenboom, F., & Frasincar, F. (2012). RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System. In Z. Gong, Y.-M. Cheung, P. Lingras, N. Zhong, P. S. Szczepaniak, & E. Suzuki (Eds.), 2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012) (pp. 74-81). IEEE Computer Society. https://doi.org/10.1109/WI-IAT.2012.63

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title = "RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System",

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.",

author = "Alexander Hogenboom and E Niewenhuijse and Frederik Hogenboom and Flavius Frasincar",

year = "2012",

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doi = "10.1109/WI-IAT.2012.63",

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RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System. / Hogenboom, Alexander; Niewenhuijse, E; Hogenboom, Frederik et al.
2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012). ed. / Z. Gong; Y.-M. Cheung; P. Lingras; N. Zhong; P.S. Szczepaniak; E. Suzuki. IEEE Computer Society, 2012. p. 74-81.

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

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T1 - RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System

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AU - Hogenboom, Frederik

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N2 - 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.

AB - 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.

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BT - 2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012)

A2 - Gong, Z.

A2 - Cheung, Y.-M.

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A2 - Szczepaniak, P.S.

A2 - Suzuki, E.

PB - IEEE Computer Society

ER -

RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System

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