Journal of Machine and Computing


Enhancing Cloud Data Deduplication with Dynamic Chunking and Public Blockchain



Journal of Machine and Computing

Received On : 11 July 2023

Revised On : 15 March 2024

Accepted On : 22 May 2024

Volume 04, Issue 03


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Abstract


The majority of cloud service providers (CSPs) store and remove customer data according to certain principles. The majority of them have designed their cloud platform to have very high levels of consistency, speed, availability, and durability. Their systems are built with these performance characteristics in mind, and the requirement to ensure precise and rapid data deletion must be carefully balanced. In the public blockchain, this paper suggests employing the rapid content-defined Chunking algorithm for data duplication. Acute data is frequently outsourced by individuals and organizations to distant cloud servers since doing so greatly reduces the headache of maintaining infrastructure and software. However, because user data is transmitted to cloud storage providers and stored on a remote cloud, ownership and control rights are nonetheless separated. Users thus have significant challenges when attempting to confirm the integrity of private information. According to the experiment results, the suggested dynamic chunking has a fast processing time that is on par with fixed-length chunking and significantly improves deduplication processing capability.


Keywords


cloud service providers (CSPs); chunking algorithm; data duplication; blockchain;


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Acknowledgements


We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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No funding was received to assist with the preparation of this manuscript.


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Cite this article


Richa Arora and Vetrithangam D, “Enhancing Cloud Data Deduplication with Dynamic Chunking and Public Blockchain”, Journal of Machine and Computing, doi: 10.53759/7669/jmc202404050.


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© 2024 Richa Arora and Vetrithangam D. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.