On routes and multicast trees in the Internet
ACM SIGCOMM Computer Communication Review
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
On the bias of traceroute sampling: or, power-law degree distributions in regular graphs
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
The internet AS-level topology: three data sources and one definitive metric
ACM SIGCOMM Computer Communication Review
Relevance of massively distributed explorations of the internet topology: qualitative results
Computer Networks: The International Journal of Computer and Telecommunications Networking
Traceroute-like exploration of unknown networks: a statistical analysis
CAAN'04 Proceedings of the First international conference on Combinatorial and Algorithmic Aspects of Networking
Describing and simulating internet routes
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
On the bias of traceroute sampling: Or, power-law degree distributions in regular graphs
Journal of the ACM (JACM)
A fast algorithm to find all high degree vertices in power law graphs
Proceedings of the 21st international conference companion on World Wide Web
A fast algorithm to find all high degree vertices in graphs with a power law degree sequence
WAW'12 Proceedings of the 9th international conference on Algorithms and Models for the Web Graph
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Traceroute sampling is an important technique in exploring the internet router graph and the autonomous system graph. Although it is one of the primary techniques used in calculating statistics about the internet, it can introduce bias that corrupts these estimates. This paper reports on a theoretical and experimental investigation of a new technique to reduce the bias of traceroute sampling when estimating the degree distribution. We develop a new estimator for the degree of a node in a traceroute-sampled graph; validate the estimator theoretically in Erdös-Rényi graphs and, through computer experiments, for a wider range of graphs; and apply it to produce a new picture of the degree distribution of the autonomous system graph.