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

Increased 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...

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Bibliographic Details
Published in2015 3rd International Conference on Signal Processing, Communication and Networking (ICSCN) pp. 1 - 6
Main Authors Sharma, Neeraj Kumar, Reddy, G. Ram Mohana
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2015
Subjects
Biological cells
Cloud Computing
Datacenter
DVFS
Energy consumption
Energy efficiency
Energy Efficient
Genetic Algorithm
Genetic algorithms
Random Allocation
Resource management
Servers
Signal processing algorithms
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DOI10.1109/ICSCN.2015.7219897

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Summary:Increased 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.
DOI:10.1109/ICSCN.2015.7219897