Energy efficient virtual machines placement in cloud datacenters using genetic algorithm and adaptive thresholds

Abdullah Alourani, Aqsa Khalid, Muhammad Tahir and Muhammad Sardaraz

PLOS ONE, 2024, vol. 19, issue 1, 1-19

Abstract: Cloud computing platform provides on-demand IT services to users and advanced the technology. The purpose of virtualization is to improve the utilization of resources and reduce power consumption. Energy consumption is a major issue faced by data centers management. Virtual machine placement is an effective technique used for this purpose. Different algorithms have been proposed for virtual machine placement in cloud environments. These algorithms have considered different parameters. It is obvious that improving one parameter affects other parameters. There is still a need to reduce energy consumption in cloud data centers. Data centers need solutions that reduce energy consumption without affecting other parameters. There is a need to device solutions to effectively utilize cloud resources and reduce energy consumption. In this article, we present an algorithm for Virtual Machines (VMs) placement in cloud computing. The algorithm uses adaptive thresholding to identify over utilized and underutilized hosts to reduce energy consumption and Service Level Agreement (SLA) violations. The algorithm is validated with simulations and comparative results are presented.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0296399 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 96399&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0296399

DOI: 10.1371/journal.pone.0296399

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().