Leveraging Data De-duplication to Improve Performance of Primary Storage Systems in the Cloud

Authors

  • R. Sadana Kumari1, P.Kumaraswamy2 Dept. of Computer Science & Engineering, SR Engineering College, Warangal, Telangana, India.

Abstract

In this paper, we tend to blessing DARE, a low-overhead deduplication-mindful similarity identification and disposal subject in an exceedingly Twin Cloud setting that successfully abuses existing copy contiguousness information for to a great degree temperate resemblance location in data deduplication based for the most part reinforcement/filing stockpiling frameworks further as backings affirmed deduplication strategy for scrambled data. The most arrangement behind DARE is to utilize a topic, choice Duplicate-Adjacency based for the most part resemblance Detection (DupAdj), by considering any two information pieces to be comparable (i.e., contender for delta compression) if their separate contiguous information lumps are copy in a deduplication framework, and after that further upgrade the likeness identification effectiveness by an enhanced super-include approach. Keywords: Data deduplication, delta pressure, stockpiling framework, record structure, execution assessment

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Published

2017-08-30

How to Cite

P.Kumaraswamy2, R. S. K. (2017). Leveraging Data De-duplication to Improve Performance of Primary Storage Systems in the Cloud. International Journal of Engineering Technology and Computer Research, 5(4). Retrieved from https://ijetcr.org/index.php/ijetcr/article/view/420

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Articles