Sampling Biases in IP Topology Measurements

— Considerable attention has been focused on the properties of graphs derived from Internet measurements. Router-level topologies collected via traceroute-like methods have led some to conclude that the router graph of the Internet is well modeled as a power-law random graph. In such a graph, the degree distribution of nodes follows a distribution with a power-law tail. We argue that the evidence to date for this conclusion is at best insufficient. We show that when graphs are sampled using traceroute-like methods, the resulting degree distribution can differ sharply from that of the underlying graph. For example, given a sparse Erd¨os-R´enyi random graph, the subgraph formed by a collection of shortest paths from a small set of random sources to a larger set of random destinations can exhibit a degree distribution remarkably like a power-law. We explore the reasons for how this effect arises, and show that in such a setting, edges are sampled in a highly biased manner. This insig...

• Type: Conference
• Year: 2003
• Where: INFOCOM
• Authors: Anukool Lakhina, John W. Byers, Mark Crovella, Peng Xie
• Keywords: Communications, Degree Distribution, INFOCOM 2003, Power-law Random Graph, Random Graph