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Conference Paper: CloudMedia: When cloud on demand meets video on demand
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TitleCloudMedia: When cloud on demand meets video on demand
 
AuthorsWu, Y1
Wu, C1
Li, B2
Qiu, X1
Lau, FCM1
 
KeywordsAlgorithm design
Client server
Computation-intensive task
Computing paradigm
Dynamic demand
 
Issue Date2011
 
PublisherIEEE, Computer Society.
 
CitationThe 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?]
DOI: http://dx.doi.org/10.1109/ICDCS.2011.50
 
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.
 
ISSN1063-6927
2013 SCImago Journal Rankings: 0.505
 
DOIhttp://dx.doi.org/10.1109/ICDCS.2011.50
 
ISI Accession Number IDWOS:000295121900026
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorWu, Y
 
dc.contributor.authorWu, C
 
dc.contributor.authorLi, B
 
dc.contributor.authorQiu, X
 
dc.contributor.authorLau, FCM
 
dc.date.accessioned2011-07-27T01:39:55Z
 
dc.date.available2011-07-27T01:39:55Z
 
dc.date.issued2011
 
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.
 
dc.description.naturepublished_or_final_version
 
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.citationThe 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?]
DOI: http://dx.doi.org/10.1109/ICDCS.2011.50
 
dc.identifier.doihttp://dx.doi.org/10.1109/ICDCS.2011.50
 
dc.identifier.epage277
 
dc.identifier.hkuros187762
 
dc.identifier.isiWOS:000295121900026
 
dc.identifier.issn1063-6927
2013 SCImago Journal Rankings: 0.505
 
dc.identifier.scopuseid_2-s2.0-80051870839
 
dc.identifier.spage268
 
dc.identifier.urihttp://hdl.handle.net/10722/135699
 
dc.languageeng
 
dc.publisherIEEE, Computer Society.
 
dc.relation.ispartofInternational Conference on Distributed Computing Systems Proceedings, ICDCS 2011
 
dc.relation.referencesReferences in Scopus
 
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 demand
 
dc.typeConference_Paper
 
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Author Affiliations
  1. The University of Hong Kong
  2. Hong Kong University of Science and Technology