%0 Journal Article %T An Example of Analyzing the Characteristics of a Large Scale ISP Topology Measured from Multiple Vantage Points
大型ISP网络拓扑多点测量及其特征分析实例 %A JIANG Yu %A FANG Bin-Xing %A HU Ming-Zeng %A HE Ren-Qing %A
姜誉 %A 方滨兴 %A 胡铭曾 %A 何仁清 %J 软件学报 %D 2005 %I %X A detailed understanding of the structural properties of Internet topology will benefit the further design and development of the Internet. It seems infeasible to study the whole Internet at router level due to its extremely large size and the difficulty in obtaining a whole topology at this level. Studying each national or continental Internet service provider (ISP) topology individually becomes an alternative method for this goal. In this paper, the measured China Education and Research Network topology, a nationwide ISP topology, is basically taken as an example. The results of mapping the topology from multiple vantage points are briefly presented. The properties of the degree distribution, large eigenvalues, and the spectral density of the measured topology graphs are analyzed. The characteristics of the signless Laplacian spectra (SLS), the normalized Laplacian spectra (NLS), and the clustering coefficients of the measured graphs are also presented. The results suggest that some power laws indeed hold in some large-scale ISP topologies; in contrast to the case of autonomous system level topologies, the power law fit is not the best choice for some ISP topologies in terms of the complementary cumulative distribution function of the degree; some real ISP topologies are a kind of scale-free graphs which are not consistent with the Barabási-Albert (BA) growth model; router level topologies are distinguishable in terms of the SLS or the NLS; router level Internet topology may have developed over time following a different set of growth processes from those of the BA model. %K Internet topology measurement %K scale-free network %K topology characteristic %K power law %K spectrum %K Laplacian eigenvalue %K clustering coefficient
Internet拓扑测量 %K 无标度网络 %K 拓扑特征 %K 幂律 %K 谱 %K 拉普拉斯特征值 %K 群集系数 %U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=DBE114DF25EED09C&yid=2DD7160C83D0ACED&vid=7801E6FC5AE9020C&iid=94C357A881DFC066&sid=5EB19D41D7A73119&eid=353B961D86F026C0&journal_id=1000-9825&journal_name=软件学报&referenced_num=24&reference_num=31