Energy Efficient Cloud Computing Vm Placement Based On Genetic Algorithm

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2017 by IJCTT Journal
Volume-44 Number-1
Year of Publication : 2017
Authors : Pooja Daharwal, Dr. Varsha Sharma
DOI :  10.14445/22312803/IJCTT-V44P103

MLA

Pooja Daharwal, Dr. Varsha Sharma   "Energy Efficient Cloud Computing Vm Placement Based On Genetic Algorithm". International Journal of Computer Trends and Technology (IJCTT) V44(1):15-23, February 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In the age of large data and the large number of users around the world, cloud computing has emerged as a new era of computing. Cloud consists of a datacenter which in turn consists of several physical machines. Each machine is shared by many users and virtual machines are used to use these physical machines. With a large number of datacenters and each datacenter having a large number of physical machines. The VM allocation becomes an NP-Hard problem. Thus, the VM allocation, the VM migration becomes a trivial task. In this article, a survey is carried out on cloud computing in energy cloud, based on scalable algorithms. To solve NP-Hard problems, there are two ways to either give an exact solution or to provide an approximation. The approximate solution is a time-efficient approach for solving NP-hard problems. In this research work, a survey on method for energy efficiency in cloud computing is carried out. The optimization of genetic algorithms has been studied in this research. And the genetic algorithm based VM placement algorithm is implemented for the energy efficiency of cloud operation.

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Keywords
Data centre, Energy Consumption, Genetic Algorithm, Virtualization, Virtual Machine (VMs), VM Placement, Cloud Computing.