Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/768
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dc.contributor.authorZhao, Yingchaoen_US
dc.contributor.otherLai, Z.-
dc.contributor.otherCui, Y.-
dc.contributor.otherBao, Y.-
dc.contributor.otherLiu, J.-
dc.contributor.otherMa, X.-
dc.date.accessioned2021-07-06T06:03:53Z-
dc.date.available2021-07-06T06:03:53Z-
dc.date.issued2015-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/768-
dc.description.abstractStreaming services are gaining popularity and have contributed a tremendous fraction of today's cellular network traffic. Both playback fluency and battery endurance are significant performance metrics for mobile streaming services. However, because of the unpredictable network condition and the loose coupling between upper layer streaming protocols and underlying network configurations, jointly optimizing rebuffering time and energy consumption for mobile streaming services remains a significant challenge. In this paper, we propose a novel framework that effectively addresses the above limitations and optimizes video transmission in cellular networks. We design two complementary algorithms, Rebuffering Time Minimization Algorithm (RTMA) and Energy Minimization Algorithm (EMA) in this framework, to achieve smoothed playback and energy-efficiency on demand over multi-user scenarios. Our algorithms integrate cross-layer parameters to schedule video delivery. Specifically, RTMA aims at achieving the minimum rebuffering time with limited energy and EMA tries to obtain the minimum energy consumption while meeting the rebuffering time constraint. Extensive simulation demonstrates that RTMA is able to reduce at least 68% rebuffering time and EMA can achieve more than 27% energy reduction compared with other state-of-the-art solutions.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.titleJoint media streaming optimization of energy and rebuffering time in cellular networksen_US
dc.typeconference proceedingsen_US
dc.relation.publication44th International Conference on Parallel Processing (ICPP 2015) Proceedingsen_US
dc.identifier.doi10.1109/ICPP.2015.49-
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.relation.isbn9781467375870en_US
dc.description.startpage400en_US
dc.description.endpage409en_US
dc.cihe.affiliatedNo-
item.languageiso639-1en-
item.openairetypeconference proceedings-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.cerifentitytypePublications-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.orcid0000-0001-8362-6735-
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