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通信网络中的负载缩放。

Scaling of load in communications networks.

作者信息

Narayan Onuttom, Saniee Iraj

机构信息

Department of Physics, University of California, Santa Cruz, California 95064, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Sep;82(3 Pt 2):036102. doi: 10.1103/PhysRevE.82.036102. Epub 2010 Sep 2.

Abstract

We show that the load at each node in a preferential attachment network scales as a power of the degree of the node. For a network whose degree distribution is p(k)∼k{-γ} , we show that the load is l(k)∼k{η} with η=γ-1 , implying that the probability distribution for the load is p(l)∼1/l{2} independent of γ . The results are obtained through scaling arguments supported by finite size scaling studies. They contradict earlier claims, but are in agreement with the exact solution for the special case of tree graphs. Results are also presented for real communications networks at the IP layer, using the latest available data. Our analysis of the data shows relatively poor power-law degree distributions as compared to the scaling of the load versus degree. This emphasizes the importance of the load in network analysis.

摘要

我们表明,在优先连接网络中,每个节点处的负载按节点度的幂次缩放。对于度分布为(p(k) \sim k^{-\gamma})的网络,我们表明负载为(l(k) \sim k^{\eta}),其中(\eta = \gamma - 1),这意味着负载的概率分布为(p(l) \sim 1/l^{2}),与(\gamma)无关。这些结果是通过有限尺寸标度研究支持的标度论证获得的。它们与早期的说法相矛盾,但与树图特殊情况的精确解一致。还使用最新可用数据给出了IP层真实通信网络的结果。我们对数据的分析表明,与负载相对于度的标度相比,度分布的幂律相对较差。这强调了负载在网络分析中的重要性。

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