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New for old: reusing ATM cell scale analysis at the burst scale

机译:旧的新增功能:在爆发规模中重用ATM细胞比例分析

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A new burst level queueing analysis has recently been published which challenges the accuracy of fluid-flow analysis for application to ATM. It is similar to the conventional approach in that it is carried out at the burst level, but differs in that the excess rate of cells is handled as a discrete process rather than as a continuous fluid. The method gives a mathematically elegant solution when the arrival process is a single on/off source: the state probabilities are a geometric progression, giving a closed form solution for the cell loss probability. This paper summarises how this new discretised fluid-flow analysis is being extended by the reuse of cell scale queueing analysis. With a single on-off source, the discretised fluid-flow analysis can be considered at the burst level as a queue with geometrically distributed batch input and geometrically distributed service time. The cell scale model provides arbitrarily distributed batch input, with batches arriving as a geometric process. This can be re-interpreted at the burst level as arbitrarily distributed excess-rate batches and geometrically distributed service times. Such a model provides an opportunity to specify more closely the excess rate arrival process and apply the analysis to multiplexing scenarios. It also enables multi-state sources to be modelled, where each one of many on states is entered from the single off state. Such sources are suitable for modelling output processes-this has potential then for extending the analysis to the network scale.
机译:最近发表了一种新的突发水平排队分析,这挑战了流体流动分析的准确性,以便应用于ATM。类似于传统方法,因为它在突发水平下进行,但是,细胞的过量速率被处理为离散的过程而不是作为连续流体。当到达过程是单个开/关源时,该方法提供了数学上优雅的解决方案:状态概率是几何进展,为细胞损耗概率提供封闭的形式解决方案。本文总结了如何通过重用细胞比例排队分析来延长这种新的离散性流体流量分析。利用单个开关源,可以在突发水平中考虑离散的流体流分析作为具有几何分布批次输入和几何分布式服务时间的队列。单元格缩放模型提供任意分布的批量输入,批次作为几何过程到达。这可以在突发级别重新解释,如任意分布的超速率批量和几何分布式服务时间。这样的模型提供了一个机会,可以更接近地指定多余的速率到达过程,并将分析应用于多路复用方案。它还支持要建模的多状态源,其中许多各个状态中的每一个都从单个关闭状态输入。这些来源适用于建模输出过程 - 这具有电位,然后将分析扩展到网络规模。

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