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Conference Paper: CloudMedia: When cloud on demand meets video on demand

TitleCloudMedia: When cloud on demand meets video on demand
Authors
KeywordsAlgorithm design
Client server
Computation-intensive task
Computing paradigm
Dynamic demand
Issue Date2011
PublisherIEEE, Computer Society.
Citation
The 31st International Conference on Distributed Computing Systems (ICDCS 2011), Minneapolis, MN., 20-24 June 2011. In Proceedings of 31st ICDCS, 2011, p. 268-277 How to Cite?
AbstractInternet-based cloud computing is a new computing paradigm aiming to provide agile and scalable resource access in a utility-like fashion. Other than being an ideal platform for computation-intensive tasks, clouds are believed to be also suitable to support large-scale applications with periods of flash crowds by providing elastic amounts of bandwidth and other resources on the fly. The fundamental question is how to configure the cloud utility to meet the highly dynamic demands of such applications at a modest cost. In this paper, we address this practical issue with solid theoretical analysis and efficient algorithm design using Video on Demand (VoD) as the example application. Having intensive bandwidth and storage demands in real time, VoD applications are purportedly ideal candidates to be supported on a cloud platform, where the on-demand resource supply of the cloud meets the dynamic demands of the VoD applications. We introduce a queueing network based model to characterize the viewing behaviors of users in a multichannel VoD application, and derive the server capacities needed to support smooth playback in the channels for two popular streaming models: client-server and P2P. We then propose a dynamic cloud resource provisioning algorithm which, using the derived capacities and instantaneous network statistics as inputs, can effectively support VoD streaming with low cloud utilization cost. Our analysis and algorithm design are verified and extensively evaluated using large-scale experiments under dynamic realistic settings on a home-built cloud platform. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/135699
ISSN
2014 SCImago Journal Rankings: 0.706
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWu, Yen_HK
dc.contributor.authorWu, Cen_HK
dc.contributor.authorLi, Ben_HK
dc.contributor.authorQiu, Xen_HK
dc.contributor.authorLau, FCMen_HK
dc.date.accessioned2011-07-27T01:39:55Z-
dc.date.available2011-07-27T01:39:55Z-
dc.date.issued2011en_HK
dc.identifier.citationThe 31st International Conference on Distributed Computing Systems (ICDCS 2011), Minneapolis, MN., 20-24 June 2011. In Proceedings of 31st ICDCS, 2011, p. 268-277en_HK
dc.identifier.issn1063-6927-
dc.identifier.urihttp://hdl.handle.net/10722/135699-
dc.description.abstractInternet-based cloud computing is a new computing paradigm aiming to provide agile and scalable resource access in a utility-like fashion. Other than being an ideal platform for computation-intensive tasks, clouds are believed to be also suitable to support large-scale applications with periods of flash crowds by providing elastic amounts of bandwidth and other resources on the fly. The fundamental question is how to configure the cloud utility to meet the highly dynamic demands of such applications at a modest cost. In this paper, we address this practical issue with solid theoretical analysis and efficient algorithm design using Video on Demand (VoD) as the example application. Having intensive bandwidth and storage demands in real time, VoD applications are purportedly ideal candidates to be supported on a cloud platform, where the on-demand resource supply of the cloud meets the dynamic demands of the VoD applications. We introduce a queueing network based model to characterize the viewing behaviors of users in a multichannel VoD application, and derive the server capacities needed to support smooth playback in the channels for two popular streaming models: client-server and P2P. We then propose a dynamic cloud resource provisioning algorithm which, using the derived capacities and instantaneous network statistics as inputs, can effectively support VoD streaming with low cloud utilization cost. Our analysis and algorithm design are verified and extensively evaluated using large-scale experiments under dynamic realistic settings on a home-built cloud platform. © 2011 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE, Computer Society.-
dc.relation.ispartofInternational Conference on Distributed Computing Systems Proceedings, ICDCS 2011en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsInternational Conference on Distributed Computing Systems Proceedings. Copyright © IEEE, Computer Society.-
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectAlgorithm design-
dc.subjectClient server-
dc.subjectComputation-intensive task-
dc.subjectComputing paradigm-
dc.subjectDynamic demand-
dc.titleCloudMedia: When cloud on demand meets video on demanden_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWu, C:cwu@cs.hku.hken_HK
dc.identifier.emailLau, FCM:fcmlau@cs.hku.hken_HK
dc.identifier.authorityWu, C=rp01397en_HK
dc.identifier.authorityLau, FCM=rp00221en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICDCS.2011.50en_HK
dc.identifier.scopuseid_2-s2.0-80051870839en_HK
dc.identifier.hkuros187762en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80051870839&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage268en_HK
dc.identifier.epage277en_HK
dc.identifier.isiWOS:000295121900026-
dc.description.otherThe 31st International Conference on Distributed Computing Systems (ICDCS 2011), Minneapolis, MN., 20-24 June 2011. In Proceedings of 31st ICDCS, 2011, p. 268-277-
dc.identifier.scopusauthoridWu, Y=47962754000en_HK
dc.identifier.scopusauthoridWu, C=15836048100en_HK
dc.identifier.scopusauthoridLi, B=36071999300en_HK
dc.identifier.scopusauthoridQiu, X=35183905700en_HK
dc.identifier.scopusauthoridLau, FCM=7102749723en_HK

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