Competitive analysis of Energy aware VW Migration Algorithms in Cloud Computing

Article Sidebar

PDF
Published: Feb 5, 2021
Keywords:
Cloud Computing VM Migration Genetic algorithm VM Placement Algorithms Virtual Machine.

Main Article Content

Navneet Singh
Vijay Dhir
Sant Baba Bhag Singh University

Abstract

The concept of Cloud Computing was first propounded by John Mc Cathy way back in 1961, wherein he envisaged the idea of computer time sharing technology. Efficient utilization of computing resources to reduce energy consumption in cloud computing is also a crucial issue because it decides the operational  cost.  Energy  consumption of  Cloud Computing  has  been  a  major  concern  of  many researchers,  and  one  of  the  reasons  for  huge  energy  consumption  of  Clouds  lies  in  the  inefficient utilization  of  computing  resources.  In  this  paper  we  perform  Competitive  Analysis  of  existing  Energy Aware  VM   Migration   Algorithms  in   Cloud   Computing.   The   aim  of   this   paper is to provide a comprehensive and comparative understanding of existing literature and aid researchers by providing an insight for potential future enhancements.

Article Details

How to Cite
Singh , N. ., & Dhir, V. . (2021). Competitive analysis of Energy aware VW Migration Algorithms in Cloud Computing. International Journal of Development Administration Research, 2(2), 36–49. retrieved from https://so02.tci-thaijo.org/index.php/ijdar/article/view/247223
Issue
Vol. 2 No. 2 (2019): (July - December 2019)
Section
Research Article

 

License Terms

All articles published in this journal are licensed under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

Under this license, users are permitted to:

  • Share — copy and redistribute the material in any medium or format.

Under the following conditions:

  1. Attribution (BY)

Users must give appropriate credit to the author(s) and the journal, provide a link to the license, and indicate if any changes were made. Attribution must not suggest endorsement by the author(s) or the journal.

  1. NonCommercial (NC)

The material may not be used for commercial purposes. Any use primarily intended for or directed toward commercial advantage or monetary compensation is prohibited without prior written permission from the copyright holder.

  1. NoDerivatives (ND)

If users remix, transform, translate, adapt, or build upon the material, they may not distribute the modified material. The work must be shared in its original and unaltered form.

This license ensures that published works remain freely accessible to the academic community and the public, while protecting the integrity of the original research and the rights of the author(s).

For the full legal code of this license, please visit:
https://creativecommons.org/licenses/by-nc-nd/4.0/