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An Evolutionary Genetic Algorithm for Optimization of Distributed Database Queries
Date
2011-05-01
Author
Sevinc, Ender
Coşar, Ahmet
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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High-performance low-cost PC hardware and high-speed LAN/WAN technologies make distributed database (DDB) systems an attractive research area where query optimization and DDB design are the two important and related problems. Since dynamic programming is not feasible for optimizing queries in a DDB, we propose a new genetic algorithm (GA)-based query optimizer (new genetic algorithm (NGA)) and compare its performance with random and optimal (exhaustive) algorithms. We perform experiments on a synthetic database with replicated relations, but no horizontal or vertical fragmentation. Network links are assumed to be gigabit ethernet. Comparisons with optimal results show that our NGA formulation performs only 20% of the optimal results and we have achieved 50% improvement over a previous GA-based algorithm.
Subject Keywords
Query optimization
,
Distributed database
,
Genetic algorithm
URI
https://hdl.handle.net/11511/29939
Journal
COMPUTER JOURNAL
DOI
https://doi.org/10.1093/comjnl/bxp130
Collections
Graduate School of Natural and Applied Sciences, Article
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BibTeX
E. Sevinc and A. Coşar, “An Evolutionary Genetic Algorithm for Optimization of Distributed Database Queries,”
COMPUTER JOURNAL
, pp. 717–725, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/29939.