On demand Virtual Machine allocation and migration at cloud data center using Hybrid of Cat Swarm Optimization and Genetic Algorithm

Simple item page
dc.contributor.authorSharma, N.K.
dc.contributor.authorGuddeti, G.R.M.
dc.date.accessioned2026-02-06T06:38:45Z
dc.date.issued2017
dc.description.abstractThis paper deals with the energy saving at the data center using energy aware Virtual Machines (VMs) allocation and migration. The multi-objective based VMs allocation using Hybrid Genetic Cat Swarm Optimization (HGACSO) algorithm saves the energy consumption as well as also reduces resource wastage. Further consolidating VMs onto the minimal number of Physical Machines (PMs) using energy efficient VMs migration, we can shut down idle PMs for enhancing the energy efficiency at a cloud data center. The experimental results show that our proposed HGACSO VM allocation and energy efficient VM migration techniques achieved the energy efficiency and minimization of resource wastage. © 2016 IEEE.
dc.identifier.citationProceedings on 5th International Conference on Eco-Friendly Computing and Communication Systems, ICECCS 2016, 2017, Vol., , p. 27-32
dc.identifier.urihttps://doi.org/10.1109/Eco-friendly.2016.7893236
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/31869
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectCat Swarm Optimization
dc.subjectEnergy Efficiency
dc.subjectGenetic Algorithm
dc.subjectResources Utilization
dc.subjectVM migration
dc.titleOn demand Virtual Machine allocation and migration at cloud data center using Hybrid of Cat Swarm Optimization and Genetic Algorithm

Files

Collections

Conference Papers