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A New Practical Packet Loss Estimator for MPLS VPN Services

机译:MPLS VPN服务的新型实用丢包估计器

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摘要

For provisioning QoS guaranteed VPN services over packet-switching networks, the service controlling system must maintain the subscribed values of QoS parameters, especially the packet loss probability, to be below a preset number. Thus one of the main issues to be solved is to estimate the packet loss accurately and effectively based on the input stochastic traffic process. Inspired by the Large Deviation Theory (LDT), two types of asymptotes loss estimator have been studied in the practical MPLS VPN networks: the large buffer asymptotic estimator (LBE) and the Aggregate Traffic approximation Estimator (ATE). However, both estimators exhibit a large error from the actual loss ratio. In this paper, a simple reactive estimator is proposed, which can adapt to the different contexts. The bask idea is to adjust the original estimator with one dynamic item that is based on the feedback of loss ratio measurement and adapt it to the changing of traffic model and buffer size. A series of experiments were devised to evaluate the performance of the new estimator under different traffic arrival models and different buffer sizes. The results show that the new practical estimator can calculate the loss probability more accurately.
机译:为了在分组交换网络上提供QoS保证的VPN服务,服务控制系统必须将QoS参数的预订值(尤其是丢包概率)保持在预设值以下。因此,要解决的主要问题之一是根据输入的随机流量过程准确而有效地估计丢包率。受大偏差理论(LDT)的启发,在实际的MPLS VPN网络中研究了两种类型的渐近线损耗估计器:大缓冲区渐近估计器(LBE)和集合流量近似估计器(ATE)。但是,两个估计器都与实际损失率相比存在较大误差。本文提出了一种简单的反应估计器,它可以适应不同的环境。晒黑的想法是用一个基于丢失率测量反馈的动态项来调整原始估算器,并使之适应流量模型和缓冲区大小的变化。设计了一系列实验,以评估在不同流量到达模型和不同缓冲区大小下新估计器的性能。结果表明,新的实用估计器可以更准确地计算损失概率。

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