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
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
On the marginal utility of network topology measurements
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Introduction to Algorithms
Exploring networks with traceroute-like probes: theory and simulations
Theoretical Computer Science - Complex networks
Relevance of massively distributed explorations of the internet topology: qualitative results
Computer Networks: The International Journal of Computer and Telecommunications Networking
On the bias of traceroute sampling: Or, power-law degree distributions in regular graphs
Journal of the ACM (JACM)
Efficient and simple generation of random simple connected graphs with prescribed degree sequence
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
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Many contributions rely on the degree distribution of the Internet topology. However, current knowledge of this property is based on biased and erroneous measurements and is subject to much debate. Recently, in [1], a new approach, referred to as the Neighborhood Flooding method, was proposed to avoid issues raised by classical measurements. It aims at measuring the neighborhood of Internet core routers by sending traceroute probes from many monitors distributed in the Internet towards a given target router. In this paper, we investigate the accuracy of this method with simulations. Our results show that Neighborhood Flooding is free from the bias highlighted in the classical approach and is able to observe properly the exact degree of a vast majority of nodes in the core of the network. We show how the quality of the estimation depends on the number of monitors used and we carefully examine the influence of parameters of the simulations on our results. We also point out some limitations of the Neighborhood Flooding method and discuss their impact on the observed distribution.