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DC Field | Value | Language |
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dc.contributor.author | Joseph, C.T. | |
dc.contributor.author | Chandrasekaran, K. | |
dc.contributor.author | Cyriac, R. | |
dc.date.accessioned | 2020-03-30T09:58:27Z | - |
dc.date.available | 2020-03-30T09:58:27Z | - |
dc.date.issued | 2015 | |
dc.identifier.citation | Procedia Computer Science, 2015, Vol.46, , pp.558-565 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/7058 | - |
dc.description.abstract | The concept of virtualization forms the heart of systems like the Cloud and Grid. Efficiency of systems that employ virtualization greatly depends on the efficiency of the technique used to allocate the virtual machines to suitable hosts. The literature contains many evolutionary approaches to solve the virtual machine allocation problem, a broad category of which employ Genetic Algorithm. This paper proposes a novel technique to allocate virtual machines using the Family Gene approach. Experimental analysis proves that the proposed approach reduces energy consumption and the rate of migrations, and hence offers much scope for future research. � 2015 Published by Elsevier B.V. | en_US |
dc.title | A novel family genetic approach for virtual machine allocation | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
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