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Conference Paper: Cost-effective low-delay cloud video conferencing

TitleCost-effective low-delay cloud video conferencing
Authors
Issue Date2015
PublisherIEEE, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/servlet/opac?punumber=1000213
Citation
The 35th IEEE International Conference on Distributed Computing Systems (ICDCS), Columbus, OH., 29 June-2 July 2015. In International Conference on Distributed Computing Systems Proceedings, 2015, p. 103-112 How to Cite?
AbstractThe cloud computing paradigm has been advocated in recent video conferencing system design, which exploits the rich on-demand resources spanning multiple geographic regions of a distributed cloud, for better conferencing experience. A typical architectural design in cloud environment is to create video conferencing agents, i.e., virtual machines, in each cloud site, assign users to the agents, and enable inter-user communication through the agents. Given the diversity of devices and network connectivities of the users, the agents may also transcode the conferencing streams to the best formats and bitrates. In this architecture, two key issues exist on how to effectively assign users to agents and how to identify the best agent to perform a transcoding task, which are nontrivial due to the following: (1) the existing proximity-based assignment may not be optimal in terms of inter-user delay, which fails to consider the whereabouts of the other users in a conferencing session; (2) the agents may have heterogeneous bandwidth and processing availability, such that the best transcoding agents should be carefully identified, for cost minimization while best serving all the users requiring the transcoded streams. To address these challenges, we formulate the user-to-agent assignment and transcoding-agent selection problems, which targets at minimizing the operational cost of the conferencing provider while keeping the conferencing delay low. The optimization problem is combinatorial in nature and difficult to solve. Using Markov approximation framework, we design a decentralized algorithm that provably converges to a bounded neighborhood of the optimal solution. An agent ranking scheme is also proposed to properly initialize our algorithm so as to improve its convergence. The results from a prototype system implementation show that our design in a set of Internet-scale scenarios reduces the operational cost by 77% as compared to a commonly-adopted alternative, while simultaneously yielding lower conferencing delays.
Persistent Identifierhttp://hdl.handle.net/10722/213559
ISSN

 

DC FieldValueLanguage
dc.contributor.authorHajiesmaili, MH-
dc.contributor.authorMak, LT-
dc.contributor.authorWang, Z-
dc.contributor.authorWu, C-
dc.contributor.authorChen, M-
dc.contributor.authorKhonsari, A-
dc.date.accessioned2015-08-05T06:55:05Z-
dc.date.available2015-08-05T06:55:05Z-
dc.date.issued2015-
dc.identifier.citationThe 35th IEEE International Conference on Distributed Computing Systems (ICDCS), Columbus, OH., 29 June-2 July 2015. In International Conference on Distributed Computing Systems Proceedings, 2015, p. 103-112-
dc.identifier.issn1063-6927-
dc.identifier.urihttp://hdl.handle.net/10722/213559-
dc.description.abstractThe cloud computing paradigm has been advocated in recent video conferencing system design, which exploits the rich on-demand resources spanning multiple geographic regions of a distributed cloud, for better conferencing experience. A typical architectural design in cloud environment is to create video conferencing agents, i.e., virtual machines, in each cloud site, assign users to the agents, and enable inter-user communication through the agents. Given the diversity of devices and network connectivities of the users, the agents may also transcode the conferencing streams to the best formats and bitrates. In this architecture, two key issues exist on how to effectively assign users to agents and how to identify the best agent to perform a transcoding task, which are nontrivial due to the following: (1) the existing proximity-based assignment may not be optimal in terms of inter-user delay, which fails to consider the whereabouts of the other users in a conferencing session; (2) the agents may have heterogeneous bandwidth and processing availability, such that the best transcoding agents should be carefully identified, for cost minimization while best serving all the users requiring the transcoded streams. To address these challenges, we formulate the user-to-agent assignment and transcoding-agent selection problems, which targets at minimizing the operational cost of the conferencing provider while keeping the conferencing delay low. The optimization problem is combinatorial in nature and difficult to solve. Using Markov approximation framework, we design a decentralized algorithm that provably converges to a bounded neighborhood of the optimal solution. An agent ranking scheme is also proposed to properly initialize our algorithm so as to improve its convergence. The results from a prototype system implementation show that our design in a set of Internet-scale scenarios reduces the operational cost by 77% as compared to a commonly-adopted alternative, while simultaneously yielding lower conferencing delays.-
dc.languageeng-
dc.publisherIEEE, Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/servlet/opac?punumber=1000213-
dc.relation.ispartofInternational Conference on Distributed Computing Systems Proceedings-
dc.rightsInternational Conference on Distributed Computing Systems Proceedings. Copyright © IEEE, Computer Society.-
dc.rights©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleCost-effective low-delay cloud video conferencing-
dc.typeConference_Paper-
dc.identifier.emailWu, C: cwu@cs.hku.hk-
dc.identifier.authorityWu, C=rp01397-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICDCS.2015.19-
dc.identifier.hkuros246585-
dc.identifier.spage103-
dc.identifier.epage112-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 150805-

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