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The paper studies the benefits of multi-path content delivery from a rate-distortion efficiency perspective. We develop an optimization framework for computing transmission schedules for streaming media packets over multiple network paths that maximize the end-to-end video quality, for the given bandwidth resources. We comprehensively address the two prospective scenarios of content delivery with packet path diversity. In the context of sender-driven systems, our framework enables the sender to compute at every transmission instance the mapping of packets to network paths that meets a rate constraint while minimizing the end-to-end distortion. In receiver-driven multi-path streaming, our framework enables the client to dynamically decide which packets, if any, to request for transmission and from which media servers, such that the end-to-end distortion is minimized for a given transmission rate constraint. Via simulation experiments, we carefully examine the performance of the scheduling framework in both multi-path delivery scenarios. We demonstrate that the optimization framework closely approaches the performance of an ideal streaming system working at channel capacity with an infinite play-out delay. We also show that the optimization leads to substantial gains in rate-distortion performance over a conventional content-agnostic scheduler. Through the concept of error-cost performance for streaming a single packet, we provide another useful insight into the operation of the optimization framework and the conventional scheduling system. (c) 2012 Elsevier Inc. All rights reserved.
Michel Bierlaire, Léa Massé Ricard
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