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2014 (Vol. 7, Issue: 14)
Article Information:

Reservation Resource Technique for Virtual Machine Placement in Cloud Data Centre

Ajith Singh. N and M. Hemalatha
Corresponding Author:  M. Hemalatha 

Key words:  Bin BECK entropy, cloud computing, energy, migration, RTBBE, SLA, virtual machine
Vol. 7 , (14): 2954-2960
Submitted Accepted Published
August 24, 2013 September 12, 2013 April 12, 2014
Abstract:

Migrations of Virtual Machine directly influence on energy consumption and QoS, to avoid migration of virtual machine when a host is overloaded a good placement technique need to be applied. Virtual Machine Placement is vital in cloud computing to utilize the resources in an efficient manner. Migration of a VM instance when a host is overloaded is familiar in cloud computing. VM selection policy finds a suitable VM to migrate from overloaded host and place to an under loaded host or turn on a new host. While migration there is small downtime of the service, even thou down time is small there is a huge change in energy consumption. Energy consumption in data centre has lead to emission of carbon dioxide to the environment. Frequent VM migration may cause the services to high latency in the network and may disturb the network environment. These works focus to reduce the VM migration, improve SLA and energy consumption. Therefore, a reservation method known as RTBBE (RTBBE (Reservation Technique Bin BECK Entropy) proposed in the study that is by allocating and assigning double upper threshold with entropy method with new overload detection PR (Polynomial Regression) and a VM selection policy MUR (Minimum Utilization Rank) had proposed in this study. The result shows that the proposed technique reduces the energy consumption, SLA and VM migration. Experimental shows that the proposed method reduce the energy up to 21.30 kWh when the overload detection PR combines with MUR, SLA of 0.00029% with IQR with MUR and 775 VM were migrated with LRR and MC.
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  Cite this Reference:
Ajith Singh. N and M. Hemalatha, 2014. Reservation Resource Technique for Virtual Machine Placement in Cloud Data Centre.  Research Journal of Applied Sciences, Engineering and Technology, 7(14): 2954-2960.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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