Design and implementation of a Bloom filter-based data deduplication algorithm for efficient data management

被引：2
|
作者：
Jang Y.-H. [1 ]
Lee N.-U. [1 ]
Kim H.-J. [1 ]
Park S.-C. [1 ]
机构：
[1] Department of IT Convergence Engineering, Gachon University, Seongnam
来源：
Journal of Ambient Intelligence and Humanized Computing | 2024年 / 15卷 / 02期
关键词：
Backup data; Bloom filters; Fast identification; Hash value; Removing duplicate data; Source-based deduplication;
D O I：
10.1007/s12652-018-0893-1
中图分类号：
学科分类号：
摘要：
Recently, the amount of data being stored has increased dramatically, and the amount of data backed up on servers increases yearly. However, the share of duplicate data in that backup data is also increasing, and because of this, the time spent on duplicate data processing is greatly increasing. Therefore, in this paper, we design a Bloom filter-based data deduplication algorithm for fast identification and removal of duplicate data. The results from evaluation of the implemented algorithm show that execution time is 17% less than with an existing deduplication algorithm. © Springer-Verlag GmbH Germany, part of Springer Nature 2018.
引用
收藏
页码：1387 / 1393
页数：6
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