论小世界网络的容量

R. Costa, J. Barros
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引用次数: 8

摘要

统计物理学的最新结果表明,大型复杂网络,无论是人工的还是自然的,都具有高聚类特性,但节点对之间的路径长度却短得惊人。打破了传统的主要依赖于与连通性直接相关的图参数的所谓小世界的方法,我们从网络信息流的角度研究了这些网络的容量。我们的贡献包括基于添加捷径的标准和可导航小世界模型的容量上限和下限,以及一些令人惊讶的结果,即在高概率下,随机重新布线不会改变小世界网络的容量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Capacity of Small-World Networks
Recent results from statistical physics show that large classes of complex networks, both man-made and of natural origin, are characterized by high clustering properties yet strikingly short path lengths between pairs of nodes. Breaking with the traditional approach to these so called small worlds that relies mainly on graph parameters directly related to connectivity, we investigate the capacity of these networks from the perspective of network information flow. Our contribution includes upper and lower bounds for the capacity of standard and navigable small-world models based on added shortcuts, and the somewhat surprising result, that, with high probability, random rewiring does not alter the capacity of a small-world network.
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