Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud Datacenter

Efficient resource allocation through Virtual machine placement in a cloud datacenter is an ever-growing demand. Different Virtual Machine optimization techniques are constructed for different optimization problems. Particle Swam Optimization (PSO) Algorithm is one of the optimization techniques to...

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Main Authors: Madhumala R. B., Tiwari Harshvardhan, Devaraj Verma C.
Format: Article
Language:English
Published: Sciendo 2021-03-01
Series:Cybernetics and Information Technologies
Subjects:
Online Access:https://doi.org/10.2478/cait-2021-0005
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author Madhumala R. B.
Tiwari Harshvardhan
Devaraj Verma C.
author_facet Madhumala R. B.
Tiwari Harshvardhan
Devaraj Verma C.
author_sort Madhumala R. B.
collection DOAJ
description Efficient resource allocation through Virtual machine placement in a cloud datacenter is an ever-growing demand. Different Virtual Machine optimization techniques are constructed for different optimization problems. Particle Swam Optimization (PSO) Algorithm is one of the optimization techniques to solve the multidimensional virtual machine placement problem. In the algorithm being proposed we use the combination of Modified First Fit Decreasing Algorithm (MFFD) with Particle Swarm Optimization Algorithm, used to solve the best Virtual Machine packing in active Physical Machines to reduce energy consumption; we first screen all Physical Machines for possible accommodation in each Physical Machine and then the Modified Particle Swam Optimization (MPSO) Algorithm is used to get the best fit solution.. In our paper, we discuss how to improve the efficiency of Particle Swarm Intelligence by adapting the efficient mechanism being proposed. The obtained result shows that the proposed algorithm provides an optimized solution compared to the existing algorithms.
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spelling doaj.art-e66a50d1ad2740788bb0f4bd671e39992022-12-21T21:23:22ZengSciendoCybernetics and Information Technologies1314-40812021-03-01211627210.2478/cait-2021-0005Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud DatacenterMadhumala R. B.0Tiwari Harshvardhan1Devaraj Verma C.2Department of Computer Science Engineering, JAIN (Deemed to be University), Bangalore, Karnataka, IndiaCIIRC, Jyothy Institute of Technology, Bangalore, Karnataka, IndiaDepartment of Computer Science Engineering, JAIN (Deemed to be University), Bangalore, Karnataka, IndiaEfficient resource allocation through Virtual machine placement in a cloud datacenter is an ever-growing demand. Different Virtual Machine optimization techniques are constructed for different optimization problems. Particle Swam Optimization (PSO) Algorithm is one of the optimization techniques to solve the multidimensional virtual machine placement problem. In the algorithm being proposed we use the combination of Modified First Fit Decreasing Algorithm (MFFD) with Particle Swarm Optimization Algorithm, used to solve the best Virtual Machine packing in active Physical Machines to reduce energy consumption; we first screen all Physical Machines for possible accommodation in each Physical Machine and then the Modified Particle Swam Optimization (MPSO) Algorithm is used to get the best fit solution.. In our paper, we discuss how to improve the efficiency of Particle Swarm Intelligence by adapting the efficient mechanism being proposed. The obtained result shows that the proposed algorithm provides an optimized solution compared to the existing algorithms.https://doi.org/10.2478/cait-2021-0005cloud computingvirtual machine optimizationparticle swarm optimization (pso)energy efficiencyresource allocationfitness function
spellingShingle Madhumala R. B.
Tiwari Harshvardhan
Devaraj Verma C.
Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud Datacenter
Cybernetics and Information Technologies
cloud computing
virtual machine optimization
particle swarm optimization (pso)
energy efficiency
resource allocation
fitness function
title Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud Datacenter
title_full Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud Datacenter
title_fullStr Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud Datacenter
title_full_unstemmed Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud Datacenter
title_short Virtual Machine Placement Using Energy Efficient Particle Swarm Optimization in Cloud Datacenter
title_sort virtual machine placement using energy efficient particle swarm optimization in cloud datacenter
topic cloud computing
virtual machine optimization
particle swarm optimization (pso)
energy efficiency
resource allocation
fitness function
url https://doi.org/10.2478/cait-2021-0005
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