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Modelling Priority Queueing Systems with Multi-Class Self-Similar Network Traffic

机译:使用多级自相似网络流量建模优先级排队系统

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Traffic self-similarity has been discovered to be a ubiquitous phenomenon in modern communication networks and multimedia systems. Due to its scale-invariant bursty nature, performance modelling of self-similar traffic poses greater challenges and exhibits more complexity than that of traditional non-bursty traffic. As a result, most existing studies on analytical modelling of priority queueing systems with self-similar inputs have been restricted to a simplified scenario where only two traffic flows are taken into account. This study contributes to performance modelling and analysis of priority queueing systems by proposing a novel and efficient queue-decomposition approach to handle multi-class self-similar traffic. Specifically, we extend the well-known method of Empty Buffer Approximation in order to decompose the priority queueing system equivalently into a group of single-server single-queue systems. We further obtain the analytical upper and lower bounds of the queue length distributions for individual traffic flows.
机译:已经发现交通自我相似性成为现代通信网络和多媒体系统中无处不在的现象。由于其规模不变的突发性,自我相似的交通的性能建模造成了更大的挑战,并且比传统的非爆发流量呈现更复杂。结果,大多数现有关于具有自相似输入的优先级排队系统的分析建模的研究已经限于简化的场景,其中仅考虑两个流量流量。本研究通过提出一种新颖的有效队列分解方法来处理优先级排队系统来处理多级自我相似流量的性能建模和分析。具体地,我们扩展了空缓冲器近似的众所周知的方法,以便等效地将优先级排队系统分解为一组单服务器单队列系统。我们进一步获得了各个流量的队列长度分布的分析上限和下限。

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