Network topology generators: degree-based vs. structural

By Hongsuda Tangmunarunkit, Ramesh Govindan, Sugih Jamin, Scott Shenker, Walter Willinger. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2002

476 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/e75149387c6a6a300a8c502572d894fd4abc72ff

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Statistical and Nonlinear Physics

Citations in the corpus

The internet AS-level topology: three data sources and one definitive metric (2005, unknown): “The Internet AS-Level Topology: Three Data Sources and One De.nitive Metric Priya Mahadevan Dmitri Krioukov UCSD CAIDA Xenofontas Dimitropoulos Georgia Tech Marina Fomenkov Bradley Huffaker CAIDA CAIDA kc claffy Amin Vahdat CAIDA UCSD {pmahadevan,vahdat}@cs.ucsd.edu,…”
Distances in Random Graphs with Finite Mean and Infinite Variance Degrees (2005, background): “In [35], it is argued on a qualitative basis that the power law random graph serves as a better model for the Internet topology than the currently used topology generators.”
Extremal Properties of Random Structures (2003, unknown): “[20]”
Resisting structural re-identification in anonymized social networks (2008, methodology): “Tree-like shortest paths We also include a graph theoretic measure called distortion,whichinsomesensecaptures how closely a graph resembles a tree [ 45 ].”
Modeling peer-peer file sharing systems (2003, background): “In a tree or a random graph, best describes their relationship [ 22 ].”
On selfish routing in Internet-like environments (2003, background): “, [9], [40]) have shown that the power-law captures the Internet structu re quite well.”
Power laws and the AS-level internet topology (2003, background): “More recently, several works have focused on describing the topology in a qualitative way [31], [32], [52], [53].”
Sampling biases in IP topology measurements (2003, background): “Our results suggest that since long-tailed degree distributions can arise simply through biased sampling of graphs, node degree distribution alone may not be a sufficiently robust metric for characterizing [7] or comparing router-level topologies [24], [25] An interesting, and seemingly very difficu”
Measuring ISP topologies with Rocketfuel (2004, methodology): “There is enough uncertainty in the properties of real ISP topologies (such as whether router outdegree distribution follows a power law as suggested by Faloutsos [8]) that it is unclear whether synthetic topologies generated by tools such as GT-ITM [28] or Brite [14] are representative [27].”
The rich-club phenomenon in the Internet topology (2003, background): “Tangmunarunkit e al [3] showed that the degree distributions produced by these structure-based generato rs re not power–laws.”
Measuring ISP topologies with rocketfuel (2002, methodology): “topologies generated by tools such as GT-ITM [26] or Brite [12] are representative [ 25 ].”
Systematic topology analysis and generation using degree correlations (2006, background): “For example, if there is only one node of high degree x and one node of another high degree y in the original graph, then there can be only one link of type (x, y).”
Graph mining: Laws, generators, and algorithms (2006, methodology): “We combine the results of several studies in the following discussion [Tangmunarunkit et al. 2001, 2002; Bu and Towsley 2002; Albert et al. 2000].”
The Internet Topology Zoo (2011, background): “We have not found any other study of the detailed statistical properties of PoP-level graphs, and there is little point in comparing apples and oranges (or apples and elephants) by comparing our results to router-level or AS-level graphs that are commonly reported in the literature (for example see ”
Inet-3.0: Internet Topology Generator (2002, background): “This metric comes from graph theory literature [4], but was related to Internet topologies in [12].”