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Internet topology at the router and autonomous system level  [PDF]
A. Vazquez,R. Pastor-Satorras,A. Vespignani
Computer Science , 2002,
Abstract: We present a statistical analysis of different metrics characterizing the topological properties of Internet maps, collected at two different resolution scales: the router and the autonomous system level. The metrics we consider allow us to confirm the presence of scale-free signatures in several statistical distributions, as well as to show in a quantitative way the hierarchical nature of the Internet. Our findings are relevant for the development of more accurate Internet topology generators, which should include, along with the scale-free properties of the connectivity distribution, the hierarchical signatures unveiled in the present work.
Spectrum Density Analysis on Router-level Internet Macroscopic Topology

XU Ye ZHAO Hai ZHANG Wen-bo,

计算机科学 , 2008,
Abstract: Analysis of spectrum density and SLS(signless Laplacian spectra) on router-level macroscopic toplogy was performed.Firstly,we found in experiments that five analysis results of spectrum density on five sampling topologies showed highly similarity proving that Internet is a system of self-similarity as well as the ability for sampling topology to resemble the whole Internet topology.Secondly,obvious difference between the spectrum density analysis results of sampling topology,ER graph and BA graph indicated ...
A Novel Methodologyof Router-To-ASMapping inspired by Community Discovery  [PDF]
Weiyi Liu,Qing Jiang,Gaolei Fei,Mingkai Yuan,Guangmin Hu
Computer Science , 2015,
Abstract: In the last decade many works has been done on the Internet topology at router or autonomous system (AS) level. As routers is the essential composition of ASes while ASes dominate the behavior of their routers. It is no doubt that identifying the affiliation between routers and ASes can let us gain a deeper understanding on the topology. However, the existing methods that assign a router to an AS just based on the origin ASes of its IP addresses, which does not make full use of information in our hand. In this paper, we propose a methodology to assign routers to their owner ASes based on community discovery tech. First, we use the origin ASes information along with router-pairs similarities to construct a weighted router level topology, secondly, for enormous topology data (more than 2M nodes and 19M edges) from CAIDA ITDK project, we propose a fast hierarchy clustering which time and space complex are both linear to do ASes community discovery, last we do router-to-AS mapping based on these ASes communities. Experiments show that combining with ASes communities our methodology discovers, the best accuracy rate of router-to-AS mapping can reach to 82.62%, which is drastically high comparing to prior works that stagnate on 65.44%.
Fractal Statistic on the Self-similarity of Internet Router-level Topology


计算机科学 , 2009,
Abstract: Because the statistical method with multi-angle and multi-measurement has many problems,a method to depict the overall Internet topology characteristics by using network fractal dimension was proposed in the paper.With the basement of the traditional fractal theory,combined with the self-similarity of Internet topology,the related concepts of the network topology dimension were given.By the mapping from Euclidean space to topology structure,the network topology dimension had been analyzed deeply and then th...
Router-level community structure of the Internet Autonomous Systems  [PDF]
Mariano G. Beiró,Sebastián P. Grynberg,J. Ignacio Alvarez-Hamelin
Computer Science , 2015, DOI: 10.1140/epjds/s13688-015-0048-y
Abstract: The Internet is composed of routing devices connected between them and organized into independent administrative entities: the Autonomous Systems. The existence of different types of Autonomous Systems (like large connectivity providers, Internet Service Providers or universities) together with geographical and economical constraints, turns the Internet into a complex modular and hierarchical network. This organization is reflected in many properties of the Internet topology, like its high degree of clustering and its robustness. In this work, we study the modular structure of the Internet router-level graph in order to assess to what extent the Autonomous Systems satisfy some of the known notions of community structure. We show that the modular structure of the Internet is much richer than what can be captured by the current community detection methods, which are severely affected by resolution limits and by the heterogeneity of the Autonomous Systems. Here we overcome this issue by using a multiresolution detection algorithm combined with a small sample of nodes. We also discuss recent work on community structure in the light of our results.
Takahiro Hirayama,Shin'ichi Arakawa,Shigehiro Hosoki,Masayuki Murata
International Journal of Computer Networks & Communications , 2011,
Abstract: Modeling the Internet is vital for network researches. Recent measurement studies on the Internet topology show that the degree distribution obeys the power-law distribution. However, only the degree distribution does not determine the performance of network control methods. As previous studies have shown, one of important factors to characterize the performance of network control methods in the Internet is a structure of topologies. However, other characteristics, which are even more important, are link capacities and node processing capacities of the network because these characteristics are particular to communication networks. In this paper, we investigate how to model the link capacity in the router-level topologies. We first reveal that the link capacity distribution of ISP’s backbone network in Japan obeys a power-law with exponent -1.1. To clarify the reason for the link capacity distribution, we evaluate throughput of networks having various kinds of link capacity distributions. Our numerical results show that the network with power-law link capacity distribution can accommodate much more traffic than the network with exponential distributions of link capacities.
Heuristically modeling method of Internet route-level topology

YANG Guo-zheng,LU Yu-liang,XIA Yang,

计算机应用研究 , 2009,
Abstract: Based on current research on Internet topology,this paper summarized a series of important characters of Internet,analyzed current Internet topology models,and pointed out that these models have some localization in describing Internet rou-ter-level topology.Then,starting from the limit factors in real router-level network,introduced the condition of generating loose network core and rewiring mechanism of preserving the node degree property,proposed a heuristically non-linear preferential attachment(HNLPA) ...
Chinese Internet AS-level Topology  [PDF]
Shi Zhou,Guo-Qiang Zhang,Guo-Qing Zhang
Computer Science , 2005, DOI: 10.1049/iet-com:20060518
Abstract: We present the first complete measurement of the Chinese Internet topology at the autonomous systems (AS) level based on traceroute data probed from servers of major ISPs in mainland China. We show that both the Chinese Internet AS graph and the global Internet AS graph can be accurately reproduced by the Positive-Feedback Preference (PFP) model with the same parameters. This result suggests that the Chinese Internet preserves well the topological characteristics of the global Internet. This is the first demonstration of the Internet's topological fractality, or self-similarity, performed at the level of topology evolution modeling.
An Improved BA Model for Router-level Internet Macroscopic Topology
IAENG International Journal of Computer Science , 2009,
Modeling the Complex Internet Topology

ZHOU Miao,YANG Jia-Hai,LIU Hong-Bo,WU Jian-Ping,
周 苗

软件学报 , 2009,
Abstract: This paper presents the basic concept of topology's properties and modeling metrics; categorizes and analyzes both AS-level models and router-lever models. Moreover, this paper summarizes current research achievements on Internet topology's modeling, especially at the router-level. Finally, it identifies future directions and open problems of the topology modeling research.

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