Novel energy efficient virtual machine allocation at data center using Genetic algorithm

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dc.contributor.authorSharma, N.K.
dc.contributor.authorGuddeti, G.
dc.date.accessioned2026-02-06T06:39:30Z
dc.date.issued2015
dc.description.abstractIncreased resources utilization from clients in a smart computing environment poses a greater challenge in allocating optimal energy efficient resources at the data center. Allocation of these optimal resources should be carried out in such a manner that we can save the energy of data center as well as avoiding the service level agreement (SLA) violation. This paper deals with the design of an energy efficient algorithm for optimized resources allocation at data center using combined approach of Dynamic Voltage Frequency Scaling (DVFS) and Genetic algorithm (GA). The performance of the proposed energy efficient algorithm is compared with DVFS. Experimental results demonstrate that the proposed energy efficient algorithm consumes 22.4% less energy over a specified workload with 0% SLA violation. © 2015 IEEE.
dc.identifier.citation2015 3rd International Conference on Signal Processing, Communication and Networking, ICSCN 2015, 2015, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/ICSCN.2015.7219897
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/32323
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectCloud Computing
dc.subjectDatacenter
dc.subjectDVFS
dc.subjectEnergy Efficient
dc.subjectGenetic Algorithm
dc.subjectRandom Allocation
dc.titleNovel energy efficient virtual machine allocation at data center using Genetic algorithm

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