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Energy Efficient VM Consolidation Technique in Cloud Computing Using Cat Swarm Optimization

  • Sudheer Mangalampalli*
  • , Kiran Sree Pokkuluri
  • , Pothuraju Raju
  • , P. J.R. Shalem Raju
  • , S. S.S.N. Usha Devi N
  • , Vamsi Krishna Mangalampalli
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Effective consolidation of VMS is necessary in cloud computing to pack and keep the VMs in the corresponding physical machines. It is a challenging task as incoming tasks are variable and changes with respect to time. To handle this scenario, a consolidation mechanism is needed to bundle the VMs in physical machines automatically without human intervention. Earlier authors proposed various consolidation mechanisms by using different heuristics and addressed metrics such as makespan, throughput, and execution time but authors have not addressed metrics named as energy consumption as it is one of the important metric in cloud computing. Minimization of energy consumption in cloud computing helpful in perspectives of both cloud user and provider. In the proposed approach, we have used cat swarm optimization algorithm to address metrics named as makespan and energy consumption and it is simulated on Cloudsim. The simulation results were compared against algorithms named as PSO and CS, and results revealed that proposed approach is showing significant impact over existing algorithms for the mentioned metrics named as makespan and energy consumption.

Original languageEnglish
Title of host publicationLecture Notes on Data Engineering and Communications Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages457-467
Number of pages11
DOIs
Publication statusPublished - 2022

Publication series

NameLecture Notes on Data Engineering and Communications Technologies
Volume132
ISSN (Print)2367-4512
ISSN (Electronic)2367-4520

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Media Technology
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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