A utilization based genetic algorithm for virtual machine placement in cloud systems

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buir.contributor.authorÇavdar, Mustafa Can
buir.contributor.authorKörpeoğlu, İbrahim
buir.contributor.authorUlusoy, Özgür
buir.contributor.orcidÇavdar, Mustafa Can|0000-0001-6743-9825
buir.contributor.orcidKörpeoğlu, İbrahim|0000-0002-0537-3848
buir.contributor.orcidUlusoy, Özgür|0000-0002-6887-3778
dc.citation.epage148en_US
dc.citation.spage136
dc.citation.volumeNumber214
dc.contributor.authorÇavdar, Mustafa Can
dc.contributor.authorKörpeoğlu, İbrahim
dc.contributor.authorUlusoy, Özgür
dc.date.accessioned2024-03-15T08:35:26Z
dc.date.available2024-03-15T08:35:26Z
dc.date.issued2024-01-15
dc.departmentDepartment of Computer Engineering
dc.description.abstractDue to the increasing demand for cloud computing and related services, cloud providers need to come up with methods and mechanisms that increase the performance, availability and reliability of data centers and cloud systems. Server virtualization is a key component to achieve this, which enables sharing of resources of a single physical machine among multiple virtual machines in a totally isolated manner. Optimizing virtualization has a very significant effect on the overall performance of a cloud computing system. This requires efficient and effective placement of virtual machines into physical machines. Since this is an optimization problem that involves multiple constraints and objectives, we propose a method based on genetic algorithms to place virtual machines into physical servers of a data center. By considering the utilization of machines and node distances, our method, called Utilization Based Genetic Algorithm (UBGA), aims at reducing resource waste, network load, and energy consumption at the same time. We compared our method against several other placement methods in terms of utilization achieved, networking bandwidth consumed, and energy costs incurred, using an open-source, publicly available CloudSim simulator. The results show that our method provides better performance compared to other placement approaches.
dc.description.provenanceMade available in DSpace on 2024-03-15T08:35:26Z (GMT). No. of bitstreams: 1 A_Utilization_Based_Genetic_Algorithm_for_virtual_machine_placement_in.pdf: 993731 bytes, checksum: 0e13c3fc8105678f813e1d67b3323cea (MD5) Previous issue date: 2024-01-15en
dc.identifier.doi10.1016/j.comcom.2023.11.028
dc.identifier.eissn1873-703X
dc.identifier.issn0140-3664
dc.identifier.urihttps://hdl.handle.net/11693/114787
dc.language.isoen
dc.relation.isversionofhttps://dx.doi.org/10.1016/j.comcom.2023.11.028
dc.rightsCC BY 4.0 DEED (Attribution 4.0 International)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.source.titleComputer Communications
dc.subjectCloud computing
dc.subjectVirtualization
dc.subjectGenetic algorithm
dc.subjectVirtual machine placement
dc.titleA utilization based genetic algorithm for virtual machine placement in cloud systems
dc.typeArticle

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