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Minimizing energy costs for geographically distributed heterogeneous data centers

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dc.contributor.authorHogade, Ninad, author
dc.contributor.authorPasricha, Sudeep, advisor
dc.contributor.authorSiegel, Howard Jay, advisor
dc.contributor.authorBurns, Patrick J., committee member
dc.date.accessioned2018-09-10T20:04:17Z
dc.date.available2018-09-10T20:04:17Z
dc.date.issued2018
dc.description.abstractThe recent proliferation and associated high electricity costs of distributed data centers have motivated researchers to study energy-cost minimization at the geo-distributed level. The development of time-of-use (TOU) electricity pricing models and renewable energy source models has provided the means for researchers to reduce these high energy costs through intelligent geographical workload distribution. However, neglecting important considerations such as data center cooling power, interference effects from task co-location in servers, net-metering, and peak demand pricing of electricity has led to sub-optimal results in prior work because these factors have a significant impact on energy costs and performance. In this thesis, we propose a set of workload management techniques that take a holistic approach to the energy minimization problem for geo-distributed data centers. Our approach considers detailed data center cooling power, co-location interference, TOU electricity pricing, renewable energy, net metering, and peak demand pricing distribution models. We demonstrate the value of utilizing such information by comparing against geo-distributed workload management techniques that possess varying amounts of system information. Our simulation results indicate that our best proposed technique is able to achieve a 61% (on average) cost reduction compared to state-of-the-art prior work.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierHogade_colostate_0053N_14871.pdf
dc.identifier.urihttps://hdl.handle.net/10217/191286
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectmemory interference
dc.subjectpeak shaving
dc.subjectgeo-distributed data centers
dc.subjectworkload management
dc.subjectnet metering
dc.titleMinimizing energy costs for geographically distributed heterogeneous data centers
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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