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Volume & Issue no: Volume 6, Issue 5, September - October 2017

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Title:
An Efficient Virtual Machine Migration Algorithm Based on Artificial intelligence
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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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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