Analysis of Availability Using Virtual Machine Placement Algorithms for Cloud IaaS

dc.contributor.advisorMesfin, Kifle (PhD)
dc.contributor.authorAmmanuel, Shawel
dc.date.accessioned2020-03-09T05:21:14Z
dc.date.accessioned2023-11-04T15:13:09Z
dc.date.available2020-03-09T05:21:14Z
dc.date.available2023-11-04T15:13:09Z
dc.date.issued2020-02
dc.description.abstractCloud Computing paradigm is most popular for its flexibility in resource provisioning by creating virtual machines of the requested specification on the underlying physical infrastructure. Infrastructure-as-a-Service, which requires a provider to allocate virtual machines (VMs), has significant impact on the availability of accommodated applications. Due to this, several algorithms have been proposed for the VM placement problem with little or no objective comparison hiding the fact which one works best or what factors influence the availability of the algorithms. In this thesis work, comparison of four algorithms using metrics of availability is presented. The findings showed that the impact of VM placement algorithms along with memory and CPU utilization play an important role in maintaining the availability of IaaS for cloud. As a result, algorithms which perform well on one metric perform poorly on the other metrics underlining the importance of objectively comparing the availability of competing algorithms and highlighting the importance of thorough empirical studies not only for power consumption and other QoS attributes but also for availability as one important aspect of cloud computing.en_US
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/21033
dc.language.isoen_USen_US
dc.publisherAddis Ababa Universityen_US
dc.subjectCloud IaaS availabilityen_US
dc.subjectvirtual machine placementen_US
dc.subjectbin packingen_US
dc.subjectheuristicsen_US
dc.titleAnalysis of Availability Using Virtual Machine Placement Algorithms for Cloud IaaSen_US
dc.typeThesisen_US

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