A Queuing Method for Adaptive Censoring in Big Data Processing

Ayesha Banu R,, Mahamat Mahmoud Salim Breck, Kamalashree M, Pavithra Rayasam,, Aruna Kumara. B


As per 2.5 quintillion bytes of information go on producing daily, the period of big data residues undeniably upon us.Running scrutiny on widespread datasets is an experiment. Luckily, an important proportion of the information accumulated can be misplaced although preserving a confident value of numerical implication in various cases. Censoring delivers us an expected choice used for data decrease. But, the information carefully preferred through censoring is not at all consistently, which force the computational amount of necessity. In this article, we suggested a lively, queuing techniques to evenly available the data’s dealing and surrendering the convergence act of censoring. The planned technique which involves simple and closed-form apprises, which does not take any kind of cost in rapports of accurateness relating towards the unique adaptive censoring technique. And we will be using the AES Algorithms to encrypting given Data form file systems and it will be uploading all files to data center using queuing model.

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DOI: https://doi.org/10.26483/ijarcs.v9i0.6246


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