A Comparative Analysis on Performance of Minimum Spanning Tree and K-Means Clustering Based Vertical Fragmentation Algorithm

Dahal, Abhishesh; Joshi, Shashidhar Ram

doi:10.1109/aitb48515.2019.8947442

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…Subsequently, a bond energy algorithm with a modified similarity measure was proposed in [39] to optimize the communication cost and storage cost. In [40], the performance of the minimum spanning tree-based fragmentation approach and K-means clustering-based fragmentation approach were compared. To reduce the communication cost during query processing, frequent access patterns were utilized in [41], and multiple fragmentation strategies were proposed.…”

Section: A Approaches For Database Fragmentationmentioning

confidence: 99%

Distributed Memetic Algorithm for Outsourced Database Fragmentation

Cao

et al. 2021

IEEE Trans. Cybern.

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Data privacy and utility are two essential requirements in outsourced data storage. Traditional techniques for sensitive data protection, such as data encryption, affect the efficiency of data query and evaluation. By splitting attributes of sensitive associations, database fragmentation techniques can help protect data privacy and improve data utility. In this article, a distributed memetic algorithm (DMA) is proposed for enhancing database privacy and utility. A balanced best random distributed framework is designed to achieve high optimization efficiency. In order to enhance global search, a dynamic grouping recombination operator is proposed to aggregate and utilize evolutionary elements; two mutation operators, namely, merge and split, are designed to help arrange and create evolutionary elements; a two-dimension selection approach is designed based on the priority of privacy and utility. Furthermore, a splicing-driven local search strategy is embedded to introduce rare utility elements without violating constraints. Extensive experiments are carried out to verify the performance of the proposed DMA. Furthermore, the effectiveness of the proposed distributed framework and novel operators is verified.

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Section: A Approaches For Database Fragmentationmentioning

confidence: 99%