Network coding is known to provide increased throughput and reduced delay for communications over networks. In this paper we propose a peer-to-peer video streaming system that exploits network coding in order to achieve low start-up delay, high streaming rate, and high resiliency to peers' dynamics. In particular, we introduce the concept of random multicast trees as overlay topology. This topology offers all benefits of tree-based overlays, notably a short start-up delay, but is much more efficient at distributing data and recovering from ungraceful peers departures. We develop a push-based streaming system that leverages network coding to efficiently distribute the information in the overlay without using buffer maps. We show performance results of the proposed system and compare it with an optimized pull systems based on Coolstreaming, showing significant improvement.

A resilient and low-delay P2P streaming system based on network coding with random multicast trees / Toldo, M.; Magli, Enrico. - (2010), pp. 400-405. (Intervento presentato al convegno IEEE International Workshop on Multimedia Signal Processing nel 2010) [10.1109/MMSP.2010.5662054].

A resilient and low-delay P2P streaming system based on network coding with random multicast trees

MAGLI, ENRICO
2010

Abstract

Network coding is known to provide increased throughput and reduced delay for communications over networks. In this paper we propose a peer-to-peer video streaming system that exploits network coding in order to achieve low start-up delay, high streaming rate, and high resiliency to peers' dynamics. In particular, we introduce the concept of random multicast trees as overlay topology. This topology offers all benefits of tree-based overlays, notably a short start-up delay, but is much more efficient at distributing data and recovering from ungraceful peers departures. We develop a push-based streaming system that leverages network coding to efficiently distribute the information in the overlay without using buffer maps. We show performance results of the proposed system and compare it with an optimized pull systems based on Coolstreaming, showing significant improvement.
2010
9781424481125
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2416526
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