Recent advances in information theory show that the throughput of a multicast session can be improved using network coding. In overlay networks, the available bandwidth between sender and different receivers are different. In this paper, we propose a solution to improve the throughput of an overlay multicast session with heterogeneous receivers by organizing the receivers into layered data distribution meshes and sending substreams to each mesh using layered coding. Our solutions utilize alternative paths and network coding in each mesh. We first formulate the problem into a mathematical programming, whose optimal solution requires global information. We therefore present a distributed heuristic algorithm. The heuristic progressively organizes the receivers into layered meshes. Each receiver can subscribe to a proper number of meshes to maximize its throughput by fully utilizing its available bandwidth. The benefits of organizing the topology into layered mesh and using network coding are demonstrated through extensive simulations. Numerical results indicate that the average throughput of a multicast session is significantly improved (up to 50% to 60%) with only slightly higher delay and network resource consumption<\/p>\n","protected":false},"excerpt":{"rendered":"
Recent advances in information theory show that the throughput of a multicast session can be improved using network coding. In overlay networks, the available bandwidth between sender and different receivers are different. In this paper, we propose a solution to improve the throughput of an overlay multicast session with heterogeneous receivers by organizing the receivers […]<\/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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13561],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[262966],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-151969","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-algorithms","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2004-5-2","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"http:\/\/www.ieee.org\/","msr_doi":"","msr_publication_uploader":"","msr_related_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/dl.acm.org\/doi\/10.1109\/TMM.2006.879847","label_id":"243112","label":0}],"msr_attachments":[{"id":0,"url":"http:\/\/www.ieee.org\/"}],"msr-author-ordering":[{"type":"text","value":"J. 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