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On the Bias of Traceroute Sampling: or, Power-Law Degree Distributions in Regular Graphs
 

Summary: 21
On the Bias of Traceroute Sampling: or, Power-Law Degree
Distributions in Regular Graphs
DIMITRIS ACHLIOPTAS
University of California, Santa Cruz
AARON CLAUSET
University of New Mexico, Albuquerque, and the Santa Fe Institute, New Mexico
DAVID KEMPE
University of Southern California, Los Angeles
AND
CRISTOPHER MOORE
University of New Mexico, Albuquerque, and the Santa Fe Institute, New Mexico
Abstract. Understanding the graph structure of the Internet is a crucial step for building accurate
network models and designing efficient algorithms for Internet applications. Yet, obtaining this graph
structure can be a surprisingly difficult task, as edges cannot be explicitly queried. For instance,
empirical studies of the network of Internet Protocol (IP) addresses typically rely on indirect methods
like traceroute to build what are approximately single-source, all-destinations, shortest-path trees.
These trees only sample a fraction of the network's edges, and a paper by Lakhina et al. [2003] found
empirically that the resulting sample is intrinsically biased. Further, in simulations, they observed
A preliminary version of this article appeared in Proceedings of the ACM Symposium on Theory of

  

Source: Achlioptas, Dimitris - Department of Computer Engineering, University of California at Santa Cruz

 

Collections: Computer Technologies and Information Sciences