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dc.contributor.authorHayes, Brian D'Angelo
dc.date.accessioned2018-08-20T15:37:00Z
dc.date.available2018-08-20T15:37:00Z
dc.date.created2018-08
dc.date.issued2018-07-10
dc.date.submittedAugust 2018
dc.identifier.urihttp://hdl.handle.net/1853/60272
dc.description.abstractThe objective of the proposed research is to develop a unique approach to efficiently deliver high-quality multimedia data by leveraging concepts from various multipath networking models in conjunction with ABR protocols that supplement the reliance on client-side network bandwidth estimation and/or buffer-state. Prior research into the development and evaluation of the performance of multipath-enabled multimedia streaming techniques are presented. Machine learning based multipath-enabled techniques are proposed in the development of selective transport protocols for streaming applications and validating their effectiveness.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectMPTCP
dc.subjectQUIC
dc.subjectSDN
dc.subjectStreaming
dc.titleEfficient delivery of multimedia content over multipath networks
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentElectrical and Computer Engineering
thesis.degree.levelDoctoral
dc.contributor.committeeMemberBeyah, Raheem
dc.contributor.committeeMemberCopeland, John
dc.contributor.committeeMemberXu, Jun
dc.contributor.committeeMemberBlough, Douglas M.
dc.date.updated2018-08-20T15:37:00Z


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