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The Minimal Buffering Requirements of Congestion Controlled Interactive Multimedia Applications

机译:拥塞控制交互式多媒体应用的最小缓冲要求

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This paper uses analysis and experiments to study the minimal buffering requirements of congestion controlled multimedia applications. Applications in the Internet must use congestion control protocols, which vary transmission rates according to network conditions. To produce a smooth perceptual quality, multimedia applications use buffering and rate adaptations to compensate these rate oscillations. While several adaptation policies are available, they require different amounts of buffering at end-hosts. We study the relationship between buffering requirements and adaptation policies. In particular, we focus on a widely pursued policy that adapts an application's sending rate exactly to the average available bandwidth to maximize throughput. Under this adaptation policy, at least a minimal amount of buffering is required to smooth the rate oscillation inherent in congestion control, and we view this minimal buffering requirement as a cost of maximizing throughput. We derive the minimal buffering requirement for this policy assuming that applications use an additive-increase-and-multiplicative-decrease (AIMD) algorithm for congestion control. The result shows the relationship between parameters of AIMD algorithms and the delay cost. We show that the buffering requirement is proportional to the parameters of the AIMD algorithm and quadratic to the application's sending rate and round-trip-time. We verify this relationship through experiments. Our results indicate that adaptation policies that maximize throughput are not suitable for interactive applications with high bit rates or long round-trip-times.
机译:本文使用分析和实验来研究拥塞控制多媒体应用的最小缓冲要求。 Internet中的应用程序必须使用拥塞控制协议,根据网络条件改变传输速率。为了产生光滑的感知质量,多媒体应用程序使用缓冲和速率适应来补偿这些速率振荡。虽然有几种适应策略可用,但它们需要在最终主机处进行不同的缓冲量。我们研究了缓冲要求与适应策略之间的关系。特别是,我们专注于广泛追求的政策,该策略适应应用程序的发送速率,完全适用于最大化吞吐量的平均可用带宽。在这种适应策略下,至少需要缓冲量的缓冲量来平滑拥塞控制中固有的速率振荡,并且我们将这种最小缓冲要求视为最大化吞吐量的成本。假设应用程序使用添加增加和乘法)用于拥塞控制的增加和乘法算法,我们推导了这一策略的最小缓冲要求。结果显示了AIMD算法参数与延迟成本之间的关系。我们表明,缓冲要求与AIMD算法的参数成比例,并与应用程序的发送速率和往返时间相反。我们通过实验验证这种关系。我们的结果表明,最大化吞吐量的适配策略不适合具有高比特率或长往返时间的交互式应用。

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