A cloud architecture for reducing costs in local parallel and distributed virtualized cloud environments

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dc.contributorHong, Xiaoyan
dc.contributorLusth, John C.
dc.contributorSmith, Randy K.
dc.contributorHu, Fei
dc.contributor.advisorVrbsky, Susan V.
dc.contributor.authorGalloway, Jeffrey Michael
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2017-03-01T16:50:11Z
dc.date.available2017-03-01T16:50:11Z
dc.date.issued2013
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractDeploying local cloud architectures can be beneficial to organizations that wish to maximize their available computational and storage resources. Many users are reluctant to move their computational and storage needs to a public cloud vendor. While designing scalable local cloud architectures, power requirements should be given adamant attention. This dissertation focuses on several challenging concerns relating to cloud computing architectures, specifically lowering the power requirements of Infrastructure-as-a-Service (IaaS) local cloud architectures. These challenges include power efficient computational resource load consolidating, power efficient persistent cloud storage consolidating, and deploying a local IaaS cloud architecture with limited networking resources. The design of a load consolidation approach to Infrastructure-as-a-Service cloud architectures that is power efficient is presented in this dissertation. A proposed Power Aware Load Consolidation algorithm, PALC, maintains the state of all compute nodes, and based on utilization percentages, decides the number of compute nodes that should be operating. Results show that PALC provides adequate availability to compute node resources while decreasing the overall power consumed by the local cloud architecture. Persistent storage is a necessity in cloud computing architectures. Since the goal of this local cloud architecture design is to deploy resources using minimum power consumption, a power aware persistent storage consolidation algorithm is presented in this dissertation. The Power Aware Storage Consolidation algorithm, PASC, dynamically determines the number or active persistent storage nodes based on the number of active users. This algorithm, combined with the PALC algorithm will significantly decrease the power consumed by the local cloud architecture. Realizing the implications of deploying a local cloud system in an environment with limited networking resources (IP addresses), a solution is needed to allow users to connect with only one public IP address. Users will be able to access cloud resources through a simple web interface and maintenance of the cloud will be contained with private networking resources. Also introduced is the ability to scale to have multiple geographically distributed clusters in the local cloud using only one IP address per cluster. This dissertation provides a comprehensive solution for deploying a local cloud architecture that is cost efficient to maintain.en_US
dc.format.extent224 p.
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otheru0015_0000001_0001347
dc.identifier.otherGalloway_alatus_0004D_11611
dc.identifier.urihttps://ir.ua.edu/handle/123456789/1814
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectComputer science
dc.titleA cloud architecture for reducing costs in local parallel and distributed virtualized cloud environmentsen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Computer Science
etdms.degree.disciplineComputer Science
etdms.degree.grantorThe University of Alabama
etdms.degree.leveldoctoral
etdms.degree.namePh.D.
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