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Modeling and queueing analysis of variable-bit-rate coded video sources in ATM networks

机译:ATM网络中可变比特率编码视频源的建模和排队分析

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Traffic models and queueing performance of variable-bit-rate (VBR) video sources in an asynchronous transfer mode (ATM) network are studied. A discrete-time discrete-state Markov chain is used to model the aggregate video traffic with each VBR-coded source being modeled by a renewal process, which has been successfully applied in the analysis of packet voice traffic. Three different methods including the stationary-interval (SI) method, the asymptotic method (ASM), and the hybrid method for queueing network analyzer (QNA) are used to approximate the average queue size. Results for different traffic conditions and different number of VBR sources are compared with the simulation results. It can be observed that as the number of sources increases the aggregate traffic becomes more predictable and the congestion at the common queue becomes smaller. This result verifies the fact that multiplexing a large number of identical video sources on a single high speed link statistically yields significant bandwidth saving. It is also interesting to note that the SI method provides an upper bound and the ASM method yields a lower bound for the average queue size for the type of traffic used in the study. When the number of VBR sources increases, the result deviates from the SI method and approaches the ASM method. In general, the QNA method provides a close match to the simulation result.
机译:研究了异步传输模式(ATM)网络中可变比特率(VBR)视频源的流量模型和排队性能。离散时间离散状态马尔可夫链用于建模总视频流量,其中每个VBR编码源都通过更新过程进行建模,该更新过程已成功应用于分组语音流量分析中。使用三种不同的方法来估计平均队列大小,这些方法包括固定间隔(SI)方法,渐近方法(ASM)和排队网络分析器的混合方法(QNA)。将不同交通状况和不同数量的VBR源的结果与仿真结果进行比较。可以观察到,随着源数量的增加,总流量变得更加可预测,并且公共队列处的拥塞变得更小。该结果验证了以下事实:在一条高速链路上多路复用大量相同的视频源,从而统计地节省了大量带宽。还有趣的是,对于研究中使用的流量类型,SI方法提供了一个上限,而ASM方法给出了一个平均队列大小的下限。当VBR源的数量增加时,结果将偏离SI方法并接近ASM方法。通常,QNA方法与仿真结果非常匹配。

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