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Statistical Analysis and Modeling of Shortest Path Lengths in Optical Transport Networks

机译:光传输网络中最短路径长度的统计分析和建模

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摘要

We analyze the shortest path lengths between node pairs of real optical transport networks. From the analysis, we find that Johnson distribution is suitable for the shortest path length modeling. The validity of the distributions is evaluated in terms of the Kolmogorov–Smirnov (KS) statistic. Johnson distribution provides an average KS statistic of 0.0423, which indicates its good accuracy. We also show that the key parameters of the shortest path lengths, such as the mean, the median, and the standard deviation, can be estimated from the convex area of the network. We develop the proposed Johnson distribution model for the shortest path lengths using the basic information of the networks. The developed model is able to estimate path-length dependent system parameters, such as the appropriate modulation formats in transparent optical networks with an average error of only . It is noteworthy that these estimations can be made without full knowledge of the network. Only the node locations are required.
机译:我们分析了实际光传输网络的节点对之间的最短路径长度。通过分析,我们发现Johnson分布适用于最短路径长度建模。根据Kolmogorov–Smirnov(KS)统计数据评估分布的有效性。 Johnson分布提供的平均KS统计量为0.0423,表明其准确性很高。我们还表明,可以从网络的凸面区域估计出最短路径长度的关键参数,例如均值,中位数和标准差。我们使用网络的基本信息为最短路径长度开发了建议的Johnson分布模型。所开发的模型能够估计路径长度相关的系统参数,例如透明光网络中的适当调制格式,平均误差仅为。值得注意的是,这些估计可以在不完全了解网络的情况下进行。仅节点位置是必需的。

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