{"id":157763,"date":"2009-06-29T00:00:00","date_gmt":"2009-06-29T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/multi-rate-peer-to-peer-video-conferencing-a-distributed-approach-using-scalable-coding\/"},"modified":"2018-10-16T20:02:10","modified_gmt":"2018-10-17T03:02:10","slug":"multi-rate-peer-to-peer-video-conferencing-a-distributed-approach-using-scalable-coding","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/multi-rate-peer-to-peer-video-conferencing-a-distributed-approach-using-scalable-coding\/","title":{"rendered":"Multi-rate Peer-to-peer Video Conferencing: A Distributed Approach Using Scalable Coding"},"content":{"rendered":"<div class=\"asset-content\">\n<p>We consider multi-rate peer-to-peer multi-party conferencing applications, where different receivers in the same group can receive videos at different rates using, for example, scalable layered coding. The quality of video received by each receiver can be modeled as a concave utility function of the video rate. We study and address the unique challenges introduced by multi-rate setting as compared to the single-rate case. We first determine an optimal set of tree structures for routing multi-rate content using scalable layered coding. We then develop Primal and Primal-dual based distributed algorithms to maximize aggregate utility of all receivers in all groups by multi-tree routing and show their convergence. These algorithms can be easily implemented and deployed on today\u2019s Internet. We have built a prototype video conferencing system to show that this approach offers low end-to-end delay, low complexity and high throughput, along with automatic adaptation to network conditions and user preferences.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We consider multi-rate peer-to-peer multi-party conferencing applications, where different receivers in the same group can receive videos at different rates using, for example, scalable layered coding. The quality of video received by each receiver can be modeled as a concave utility function of the video rate. We study and address the unique challenges introduced by [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"IEEE","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"2009 IEEE International Conference on Multimedia and Expo","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"\u00a9 2008 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.http:\/\/www.ieee.org\/","msr_conference_name":"2009 IEEE International Conference on Multimedia and Expo","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Miroslav Ponec, Philip A. 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