Affiliations: [a] Department of Computer Science and Engineering and Information Technology, School of Technology, Assam Don Bosco University, Assam, India | [b] School of Computing, Teesside University, Middlesbrough, UK
Correspondence:
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Corresponding author: Esha Barlaskar, Department of Computer Science and Engineering and Information Technology, School of Technology, Assam Don Bosco University, Assam, India. E-mail:[email protected]
Abstract: The consolidation of the virtual machines (VMs) helps to optimise the usage
of resources and hence reduces the energy consumption in a cloud data
centre. VM placement plays an important part in the consolidation of the
VMs. The researchers have developed various algorithms for VM placement
considering the optimised energy consumption. However, these algorithms lack
the use of exploitation mechanism efficiently. This paper addresses VM
placement issues by proposing two meta-heuristic algorithms namely, the
enhanced modified firefly algorithm (MFF) and the hierarchical cluster based
modified firefly algorithm (HCMFF), presenting the comparative analysis
relating to energy optimisation. The comparisons are made against the
existing honeybee (HB) algorithm, honeybee cluster based technique (HCT) and
the energy consumption results of all the participating algorithms confirm
that the proposed HCMFF is more efficient than the other algorithms. The
simulation study shows that HCMFF consumes 12% less energy than honeybee
algorithm, 6% less than HCT algorithm and 2% less than original
firefly. The usage of the appropriate algorithm can help in efficient usage
of energy in cloud computing.
