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Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique

Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique

Van Nghia Luong, Vijender Kumar Solanki, Nguyen Ha Huy Cuong
Copyright: © 2019 |Volume: 9 |Issue: 2 |Pages: 10
ISSN: 2155-6377|EISSN: 2155-6385|EISBN13: 9781522567158|DOI: 10.4018/IJIRR.2019040103
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MLA

Luong, Van Nghia, et al. "Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique." IJIRR vol.9, no.2 2019: pp.28-37. http://doi.org/10.4018/IJIRR.2019040103

APA

Luong, V. N., Solanki, V. K., & Cuong, N. H. (2019). Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique. International Journal of Information Retrieval Research (IJIRR), 9(2), 28-37. http://doi.org/10.4018/IJIRR.2019040103

Chicago

Luong, Van Nghia, Vijender Kumar Solanki, and Nguyen Ha Huy Cuong. "Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique," International Journal of Information Retrieval Research (IJIRR) 9, no.2: 28-37. http://doi.org/10.4018/IJIRR.2019040103

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Abstract

Distributed database design solutions depend heavily on the exploitation of input data sources by using clustering techniques in data mining. A new approach of biomimetic computation systems such as ant colony optimization (ACO) for this solution is of interest to informatics experts. Using ACO techniques for this solution has the advantages such as faster algorithms thanks to the randomness of ant colony behavior. The use of random numbers based on heuristic information to pickup (drop) points will facilitate the flexible search on a large data space, so that it provides us with a better answer. In this article, the authors present ACO algorithms application solutions to clustering techniques for the problem of vertical fragmentation of distributed data.

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