Multi-path content delivery: Efficiency analysis and optimization algorithms

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.

► We studied the benefits of multi-path content delivery from an R–D perspective.
► We developed an optimization framework for computing transmission schedules.
► We closely approach the performance of an ideal streaming system.
► Substantial gains in R–D performance over a conventional scheduler are achieved.
► The concept of error-cost for streaming a single packet provides further insights.