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11.12.2018

An Energy-Efficient Dynamic Resource Management Approach Based on Clustering and Meta-Heuristic Algorithms in Cloud Computing IaaS Platforms

Energy Efficient Dynamic Cloud Resource Management

verfasst von: Maryam Askarizade Haghighi, Mehrdad Maeen, Majid Haghparast

Erschienen in: Wireless Personal Communications | Ausgabe 4/2019

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Abstract

Cloud computing as an emerging technology, has revolutionized the information technology industry by elastic on-demand provisioning and De-provisioning of computing resources. Due to the huge amount of electrical energy consumption by large-scale Datacenters, it is essential to investigate various approaches in order to decrease simultaneously energy and its impacts on global economic crisis and ecological concerns. This study through virtualization technique applied a hybrid technique for resource management. This technique used k-means clustering for mapping task and dynamic consolidation method, which improved by micro-genetic algorithm. Experimental evaluation performed on CloudSim 3.0.3 and the results were analyzed with Expert-Choice software tools. We found that the proposed KMGA technique could provide a good trade-off between effectively reduce energy consumption of Datacenters and sustained quality of service. In addition, it minimized the number of virtual machine migrations and make-span, in comparison with particle swarm optimization and genetic algorithms in similar hybrid techniques.

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Titel: An Energy-Efficient Dynamic Resource Management Approach Based on Clustering and Meta-Heuristic Algorithms in Cloud Computing IaaS Platforms
Energy Efficient Dynamic Cloud Resource Management
verfasst von: Maryam Askarizade Haghighi
Mehrdad Maeen
Majid Haghparast
Publikationsdatum: 11.12.2018
Verlag: Springer US
Erschienen in: Wireless Personal Communications / Ausgabe 4/2019
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-018-6089-3

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