An Evolutionary Genetic Algorithm for Optimization of Distributed Database Queries

Date

2011-05-01

Author

Sevinc, Ender
Coşar, Ahmet

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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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Citation Formats

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.