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The influence of burstiness and correlation of traffic on an ATM multiplexer

机译:业务量突发性和相关性对ATM多路复用器的影响

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This paper presents a traffic model for an ATM multiplexer providing video, voice, image, and data services. The traffic model classifies the input traffic into two types: real-time and non-real-time. The input process for real-time traffic is a Markov modulated Bernoulli process (MMBP), while that for non-real-time traffic is a Bernoulli process with batches. The z-transform of the cell interarrival time A/sub MMBP/(z) is obtained. The average traffic load /spl rho//sub MMBP/ and the squared coefficient of variation of the time between success cell C/sup 2//sub MMBP/ are then obtained from the respective derivatives of A/sub MMBP/(z). The autocorrelation coefficient of the cell interarrival time with lag 1 /spl psi/, can be also obtained. This paper presents an iterative algorithm that can be used to calculate the MMBP probability distribution of the cell interarrival time. So far few results about discrete-time finite buffer queues with correlated inputs are known. This paper analyzes the performance of an ATM multiplexer considering the correlation and burst in cell arrivals. For the MMBP-stream, the waiting time distribution and the cell loss probability for MMBP+M/sup [X]//D/1/K finite buffer system are all exactly calculated with the use of a recursive algorithm. Calculations show the influence of burstiness and correlation on both the loss probability and waiting time. The accuracy of the analytical results has been largely validated by means of a simulation approach.
机译:本文介绍了提供视频,语音,图像和数据服务的ATM多路复用器的流量模型。流量模型将输入流量分为两种类型:实时和非实时。实时流量的输入过程是马尔可夫调制的伯努利过程(MMBP),而非实时流量的输入过程是具有批次的伯努利过程。获得单元格到达时间A / sub MMBP /(z)的z变换。然后,从A / sub MMBP /(z)的各个导数获得平均业务负载/ spl rho // sub MMBP /和成功单元格C / sup 2 // sub MMBP /之间的时间变化的平方系数。还可以得到滞后时间为1 / spl psi /的信元到达时间的自相关系数。本文提出了一种迭代算法,可用于计算单元格到达时间的MMBP概率分布。到目前为止,关于具有相关输入的离散时间有限缓冲区队列的结果知之甚少。考虑到信元到达的相关性和突发,本文分析了ATM多路复用器的性能。对于MMBP流,使用递归算法精确计算MMBP + M / sup [X] // D / 1 / K有限缓冲系统的等待时间分布和信元丢失概率。计算显示了突发性和相关性对丢失概率和等待时间的影响。分析结果的准确性已通过模拟方法得到了充分验证。

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