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DOI: 10.14569/IJACSA.2016.071121
PDF

Qos-based Computing Resources Partitioning between Virtual Machines in the Cloud Architecture

Author 1: Evgeny Nikulchev
Author 2: Evgeniy Pluzhnik
Author 3: Oleg Lukyanchikov
Author 4: Dmitry Biryukov
Author 5: Elena Andrianova

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 11, 2016.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Cloud services have been used very widely, but configuration of the parameters, including the efficient allocation of resources, is an important objective for the system architect. The article is devoted to solving the problem of choosing the architecture of computers based on simulation and developed program for monitoring computing resources. Techniques were developed aimed at providing the required quality of service and efficient use of resources. The article describes the monitoring program of computing resources and time efficiency of the target application functions. On the basis of this application the technique is shown and described in the experiment, designed to ensure the requirements for quality of service, by isolating one process from the others on different virtual machines inside the hypervisor.

Keywords: cloud computing architecture; simulation; software for monitoring computer resources

Evgeny Nikulchev, Evgeniy Pluzhnik, Oleg Lukyanchikov, Dmitry Biryukov and Elena Andrianova, “Qos-based Computing Resources Partitioning between Virtual Machines in the Cloud Architecture” International Journal of Advanced Computer Science and Applications(IJACSA), 7(11), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071121

@article{Nikulchev2016,
title = {Qos-based Computing Resources Partitioning between Virtual Machines in the Cloud Architecture},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071121},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071121},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {11},
author = {Evgeny Nikulchev and Evgeniy Pluzhnik and Oleg Lukyanchikov and Dmitry Biryukov and Elena Andrianova}
}



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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