自治系统网络拓扑演化研究

Yue Zhang, Guozheng Yang, Zhihao Luo
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引用次数: 0

摘要

在对自主系统级网络的研究进行调查后,我们发现使用的最新数据分析是2013年提供的开放数据。因此,本文以RouteViews提供的2000 - 2020年的开源网络BGP路由信息为基础,结合复杂网络的研究理论和方法,设计了自治系统级网络拓扑特征参数的计算和分析方法。利用这些方法,每月从全球和国家层面计算自治系统级网络的规模和拓扑特征参数。分析了近21年来网络规模和拓扑特征的演变。通过分析连接数、网段数、IP地址数、节点数、核心数、中间数、路径平均长度等的演变规律。总结了网络演化的一些规律。首先,网络的某些特征彼此之间具有很强的相关性。自2012年起,这类节点恢复了其在网络中的主体地位,其度数为1,因为网络发展较晚的国家节点的影响力逐渐增强。民族自治系统网络特征的演变与全球网络具有自相似性,但在不同国家又存在一定差异。这些结论为宏观层面理解互联网的拓扑特征和进一步推断其演化趋势提供了方法支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Topology Evolution of Autonomous System Network
After investigating the study about autonomous system level networks, we found that the latest data analysis used is open data provided in 2013. Thus, based on the open-source network BGP routing information provided by RouteViews from 2000 to 2020, this paper designs the calculation and analysis methods of the topological characteristic parameters of autonomous system level network combing the research theories and methods of Complex Network. Using these methods, the scale and topological characteristic parameters of the autonomous system-level network are calculated monthly from the global level and the national levels. And the evolution of the network scale and topological characteristics in the past 21 years are analyzed. Through analyzing the evolution of the number of connections, the number of network segments, the number of IP addresses, the number of nodes, the number of cores, the number of betweenness, and the average length of the path, and so on. Some regularities of network evolution are summarized. Firstly, some characteristics of the network are strongly correlated with each other. Since 2012, this kind of node has resumed its main part in the network whose number of degrees is 1, because the nodes of countries with late network development have gradually increased their influence. The evolution of the national autonomous system network characteristics is self-similar to the global network, but there are certain differences in different countries. These conclusions provide method support for the macro-level understanding of the Internet's topological characteristics and further inference of its evolutionary trend.
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