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Measurement based optimal source shaping with a shaping + multiplexing delay constraint

机译:具有整形+多路复用延迟约束的基于测量的最佳源整形

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Most on-line (i.e., not stored) variable bit rate sources would find it difficult to a priori declare the traffic parameters required by a connection admission control strategy. There is thus the problem of measurement-based on-line estimation of source parameters. In this paper we address the problem of selection of source parameters based on minimising a buffer-bandwidth cost function in the network, for a specified delay QoS violation probability. We consider the shaping delay plus first-hop multiplexing delay; this is adequate, for example, for n statistically identical packet voice sources being multiplexed at a PBX, or in approaches where the end-to-end delay bound is broken into per-hop delay bounds. Our approach yields a leaky bucket rate parameter /spl rho//sup */, and the sum of the shaper buffer and leaky bucket depth (B/sub s/+/spl sigma/). We show that, for a fluid source model, for a linear buffer-bandwidth cost function, and for lossless multiplexing, a sustainable rate parameter of /spl rho//sup */ and burst parameter of 0 yields the minimum cost. We propose and study a stochastic approximation algorithm for on-line estimation of /spl rho//sup */. We then use buffer-bandwidth cost considerations to arrive at an optimal leaky bucket depth /spl sigma//sup */<0 for lossy multiplexing of several statistically identical sources. The computation of /spl sigma//sup */ must be done at the network node. We show, by an example, the improvement in cost that is possible by lossy multiplexing and a positive /spl sigma//sup */.
机译:大多数在线(即,未存储的)可变比特率源将发现很难先验地声明连接接纳控制策略所需的业务参数。因此存在源参数的基于测量的在线估计的问题。在本文中,我们针对指定的延迟QoS违规概率,基于最小化网络中的缓冲区带宽代价函数,解决了选择源参数的问题。我们考虑整形延迟加上第一跳多路复用延迟;例如,这对于在PBX上多路复用n个统计上相同的分组语音源或在将端到端延迟界限分为每跳延迟界限的方法中就足够了。我们的方法产生漏斗速率参数/ spl rho // sup * /,以及整形器缓冲区和漏斗深度的总和(B / sub s / + / spl sigma /)。我们表明,对于流体源模型,线性缓冲区带宽成本函数和无损多路复用,可持续速率参数/ spl rho // sup * /和突发参数0产生的最低成本。我们提出并研究了用于/ spl rho // sup * /在线估计的随机近似算法。然后,我们使用缓冲区带宽成本考虑因素,为几个统计上相同的源进行有损复用,从而获得最佳泄漏桶深度/ spl sigma // sup * / <0。 / spl sigma // sup * /的计算必须在网络节点上进行。举例说明,通过有损复用和正数/ spl sigma // sup * /可以实现成本的改善。

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