Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01j9602354g
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorWentzlaff, David-
dc.contributor.authorShahrad, Mohammad-
dc.contributor.otherElectrical Engineering Department-
dc.date.accessioned2020-07-13T03:33:33Z-
dc.date.available2020-07-13T03:33:33Z-
dc.date.issued2020-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01j9602354g-
dc.description.abstractCloud computing plays an integral role in almost every aspect of today's IT-driven society. The ever-increasing scale and complexity of public cloud infrastructure, together with the wide range of services enabled by it, make it easy to leave efficiency behind. Efficiency has always been crucial for cloud providers due to the massive capital expenditure. However, it has become much more relevant as the free ride of Moore's Law and Dennard Scaling is nearing an end. This dissertation explores various ways to increase the efficiency of future public cloud systems. The proposed solutions span across deployment models, resource management policies, and microarchitectural changes. A primary conclusion of this dissertation is the importance of vertical integration in ensuring high efficiency. Moreover, it is essential to consider user behavior and put incentives in place for them to use cloud services efficiently.-
dc.language.isoen-
dc.publisherPrinceton, NJ : Princeton University-
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=http://catalog.princeton.edu> catalog.princeton.edu </a>-
dc.subjectcloud computing-
dc.subjectfunction as a service-
dc.subjectinfrastructure as a service-
dc.subjectresource management-
dc.subjectresource scheduling-
dc.subjectserverless computing-
dc.subject.classificationComputer engineering-
dc.subject.classificationComputer science-
dc.subject.classificationElectrical engineering-
dc.titleResource-Efficient Management of Large-Scale Public Cloud Systems-
dc.typeAcademic dissertations (Ph.D.)-
Appears in Collections:Electrical Engineering

Files in This Item:
File Description SizeFormat 
Shahrad_princeton_0181D_13410.pdf14.5 MBAdobe PDFView/Download


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.