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DOI: 10.14569/IJACSA.2015.060603
PDF

Experimental Study of the Cloud Architecture Selection for Effective Big Data Processing

Author 1: Evgeny Nikulchev
Author 2: Evgeniy Pluzhnik
Author 3: Dmitry Biryukov
Author 4: Oleg Lukyanchikov
Author 5: Simon Payain

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 6, 2015.

  • Abstract and Keywords
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Abstract: Big data dictate their requirements to the hardware and software. Simple migration to the cloud data processing, while solving the problem of increasing computational capabilities, however creates some issues: the need to ensure the safety, the need to control the quality during data transmission, the need to optimize requests. Computational cloud does not simply provide scalable resources but also requires network infrastructure, unknown routes and the number of user requests. In addition, during functioning situation can occur, in which you need to change the architecture of the application — part of the data needs to be placed in a private cloud, part in a public cloud, part stays on the client.

Keywords: Cloud Infrastructure; Big Data; Distributed Databases; Hybrid Clouds

Evgeny Nikulchev, Evgeniy Pluzhnik, Dmitry Biryukov, Oleg Lukyanchikov and Simon Payain. “Experimental Study of the Cloud Architecture Selection for Effective Big Data Processing”. International Journal of Advanced Computer Science and Applications (IJACSA) 6.6 (2015). http://dx.doi.org/10.14569/IJACSA.2015.060603

@article{Nikulchev2015,
title = {Experimental Study of the Cloud Architecture Selection for Effective Big Data Processing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060603},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060603},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {6},
author = {Evgeny Nikulchev and Evgeniy Pluzhnik and Dmitry Biryukov and Oleg Lukyanchikov and Simon Payain}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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