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

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dc.contributor Hong, Xiaoyan
dc.contributor Lusth, John C.
dc.contributor Smith, Randy K.
dc.contributor Hu, Fei
dc.contributor.advisor Vrbsky, Susan V.
dc.contributor.author Galloway, Jeffrey Michael
dc.contributor.other University of Alabama Tuscaloosa
dc.date.accessioned 2017-03-01T16:50:11Z
dc.date.available 2017-03-01T16:50:11Z
dc.date.issued 2013
dc.identifier.other u0015_0000001_0001347
dc.identifier.other Galloway_alatus_0004D_11611
dc.identifier.uri https://ir.ua.edu/handle/123456789/1814
dc.description Electronic Thesis or Dissertation en_US
dc.description.abstract Deploying 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.extent 224 p.
dc.format.medium electronic
dc.format.mimetype application/pdf
dc.language English
dc.language.iso en_US
dc.publisher University of Alabama Libraries
dc.relation.ispartof The University of Alabama Electronic Theses and Dissertations
dc.relation.ispartof The University of Alabama Libraries Digital Collections
dc.relation.hasversion born digital
dc.rights All rights reserved by the author unless otherwise indicated. en_US
dc.subject Computer science
dc.title A cloud architecture for reducing costs in local parallel and distributed virtualized cloud environments en_US
dc.type thesis
dc.type text
etdms.degree.department University of Alabama. Department of Computer Science
etdms.degree.discipline Computer Science
etdms.degree.grantor The University of Alabama
etdms.degree.level doctoral
etdms.degree.name Ph.D.

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