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The Journal of Supercomputing

Erschienen in:

20.12.2017

Data deduplication techniques for efficient cloud storage management: a systematic review

verfasst von: Ravneet Kaur, Inderveer Chana, Jhilik Bhattacharya

Erschienen in: The Journal of Supercomputing | Ausgabe 5/2018

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Abstract

The exponential growth of digital data in cloud storage systems is a critical issue presently as a large amount of duplicate data in the storage systems exerts an extra load on it. Deduplication is an efficient technique that has gained attention in large-scale storage systems. Deduplication eliminates redundant data, improves storage utilization and reduces storage cost. This paper presents a broad methodical literature review of existing data deduplication techniques along with various existing taxonomies of deduplication techniques that have been based on cloud data storage. Furthermore, the paper investigates deduplication techniques based on text and multimedia data along with their corresponding taxonomies as these techniques have different challenges for duplicate data detection. This research work is useful to identify deduplication techniques based on text, image and video data. It also discusses existing challenges and significant research directions in deduplication for future researchers, and article concludes with a summary of valuable suggestions for future enhancements in deduplication.

Vorheriger Artikel A graph-based cache for large-scale similarity search engines

Nächster Artikel A survey of graph processing on graphics processing units

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Titel: Data deduplication techniques for efficient cloud storage management: a systematic review
verfasst von: Ravneet Kaur
Inderveer Chana
Jhilik Bhattacharya
Publikationsdatum: 20.12.2017
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 5/2018
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-017-2210-8

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