Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique

Luong Van Nghia, Vijender Kumar Solanki and Nguyen Ha Huy Cuong
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Luong Van Nghia: Pham Van Dong University, Quang Ngai, Vietnam
Vijender Kumar Solanki: CMR institute of Technology (Autonomous), Hyderabad, India
Nguyen Ha Huy Cuong: Quang Nam University, Tam Ky, Vietnam

International Journal of Information Retrieval Research (IJIRR), 2019, vol. 9, issue 2, 28-37

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.

Date: 2019
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