International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org
Call for Paper, Published Articles, Indexing Infromation
Title: |
An Efficient Virtual Machine Migration Algorithm Based on Artificial intelligence
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Author Name: |
Navdeep Kaur, Pooja Nagpal |
Abstract: |
Abstract: Cloud computing has brought a revolution in the
domain of computing. Numerous algorithms are proposed to
perform it more effectively. In cloud computing, Virtualization
plays a significant role and entire performance of cloud
depends on VM allocation and Migration. As many of energy
are absorbed in this technology so different algorithms will be
used to save energy and enhance the efficiency of proposed
work known as Green algorithms. In this research work, a
green algorithm for VM Migration is introduced using
metaheuristic algorithm named as Genetic algorithm (GA).
Every server has to perform different or same functions. A
cloud computing infrastructure can be model as PM is a set of
physical Servers/host PM1, PM2, PM3… PMn. The resources
of cloud infrastructure can be used by the virtualization
technology, which allows one to create several VMs on a
physical server/host and therefore, reduces amount of hardware
in use and improves the utilization of resources. The computing
resource/node in cloud is used through the virtual machine. To
address this problem, data centre resources need to be managed
in resource -efficient manner to drive Green Cloud computing
has been proposed in this work using Virtual machine concept
with Genetic algorithm (GA). All the simulations have been
carried out in CLOUDSIM environment and the parameters
like SLA violations, Energy consumption and VM migrations
along with their comparison with existing techniques will be
performed.
Keywords: Virtual machine, VM migrations, Green cloud
computing, Genetic algorithm (GA) |
Cite this article: |
Navdeep Kaur, Pooja Nagpal , "
An Efficient Virtual Machine Migration Algorithm Based on Artificial intelligence " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS),
Volume 6, Issue 5, September - October 2017 , pp.
178-183 , ISSN 2278-6856.
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