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Distributed optimization of P2P live streaming overlays
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.ORCID iD: 0000-0002-9484-6714
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.ORCID iD: 0000-0002-6718-0144
2012 (English)In: Computing, ISSN 0010-485X, Vol. 94, no 8/10, 621-647 p.Article in journal (Refereed) Published
Abstract [en]

Peer-to-peer live media streaming over the Internet is becoming increasingly more popular, though it is still a challenging problem. Nodes should receive the stream with respect to intrinsic timing constraints, while the overlay should adapt to the changes in the network and the nodes should be incentivized to contribute their resources. In this work, we meet these contradictory requirements simultaneously, by introducing a distributed market model to build an efficient overlay for live media streaming. Using our market model, we construct two different overlay topologies, tree-based and mesh-based, which are the two dominant approaches to the media distribution. First, we build an approximately minimal height multiple-tree data dissemination overlay, called Sepidar. Next, we extend our model, in GLive, to make it more robust in dynamic networks by replacing the tree structure with a mesh. We show in simulation that the mesh-based overlay outperforms the multiple-tree overlay. We compare the performance of our two systems with the state-of-the-art NewCoolstreaming, and observe that they provide better playback continuity and lower playback latency than that of NewCoolstreaming under a variety of experimental scenarios. Although our distributed market model can be run against a random sample of nodes, we improve its convergence time by executing it against a sample of nodes taken from the Gradient overlay. The evaluations show that the streaming overlays converge faster when our market model works on top of the Gradient overlay.

Place, publisher, year, edition, pages
2012. Vol. 94, no 8/10, 621-647 p.
Keyword [en]
Auction algorithm, Distributed algorithms, Market-based algorithms, P2P live streaming, The Gradient overlay
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-107416DOI: 10.1007/s00607-012-0195-yISI: 000307971700002OAI: oai:DiVA.org:kth-107416DiVA: diva2:575848
Funder
Swedish eā€Science Research CenterICT - The Next Generation
Note

QC 20130115

Available from: 2012-12-11 Created: 2012-12-11 Last updated: 2014-01-27Bibliographically approved

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Dowling, JimHaridi, Seif

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