Exploring networks with traceroute-like probes: theory and simulations

Mapping the Internet generally consists in sampling the network from a limited set of sources by using traceroute-like probes. This methodology, akin to the merging of different spanning trees to a set of destination, has been argued to introduce uncontrolled sampling biases that might produce statistical properties of the sampled graph which sharply differ from the original ones. In this paper, we explore these biases and provide a statistical analysis of their origin. We derive an analytical approximation for the probability of edge and vertex detection that exploits the role of the number of sources and targets and allows us to relate the global topological properties of the underlying network with the statistical accuracy of the sampled graph. In particular, we find that the edge and vertex detection probability depends on the betweenness centrality of each element. This allows us to show that shortest path routed sampling provides a better characterization of underlying graphs wi...

• Type: Journal
• Year: 2004
• Where: CORR
• Authors: Luca Dall'Asta, J. Ignacio Alvarez-Hamelin, Alain Barrat, Alexei Vázquez, Alessandro Vespignani
• Keywords: CORR 2004, Education, Statistical Properties, Uncontrolled Sampling Biases, Vertex Detection