Abstract
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.
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