Lava: A Reality Check of Network Coding in Peer-to-Peer Live Streaming
In recent literature, network coding has emerged as a promising information theoretic approach to improve the performance of both peer-to-peer and wireless networks. It has been widely accepted and acknowledged that network coding can theoretically improve network throughput of multicast sessions in...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | In recent literature, network coding has emerged as a promising information theoretic approach to improve the performance of both peer-to-peer and wireless networks. It has been widely accepted and acknowledged that network coding can theoretically improve network throughput of multicast sessions in directed acyclic graphs, achieving their cut-set capacity bounds. Recent studies have also supported the claim that network coding is beneficial for large-scale peer-to-peer content distribution, as it solves the problem of locating the last missing blocks to complete the download. We seek to perform a reality check of using network coding for peer-to-peer live multimedia streaming. We start with the following critical question: How helpful is network coding in peer-to-peer streaming? To address this question, we first implement the decoding process using Gauss-Jordan elimination, such that it can be performed while coded blocks are progressively received. We then implement a realistic testbed, called Lava, with actual network traffic to meticulously evaluate the benefits and tradeoffs involved in using network coding in peer-to-peer streaming. We present the architectural design challenges in implementing network coding for the purpose of streaming, along with a pull-based peer-to-peer live streaming protocol in our comparison studies. Our experimental results show that network coding makes it possible to perform streaming with a finer granularity, which reduces the redundancy of bandwidth usage, improves resilience to network dynamics, and is most instrumental when the bandwidth supply barely meets the streaming demand. |
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ISSN: | 0743-166X 2641-9874 |
DOI: | 10.1109/INFCOM.2007.130 |