A critical point for random graphs with a given degree sequence
Random Graphs 93 Proceedings of the sixth international seminar on Random graphs and probabilistic methods in combinatorics and computer science
A quantitative comparison of graph-based models for Internet topology
IEEE/ACM Transactions on Networking (TON)
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
The diameter of random massive graphs
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
On the marginal utility of network topology measurements
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Analysis of the autonomous system network topology
ACM SIGCOMM Computer Communication Review
On the origin of power laws in Internet topologies
ACM SIGCOMM Computer Communication Review
Measuring ISP topologies with rocketfuel
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Heuristically Optimized Trade-Offs: A New Paradigm for Power Laws in the Internet
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Influence of Network Topology on Protocol Simulation
ICN '01 Proceedings of the First International Conference on Networking-Part 1
Internet Topology Modeler Based on Map Sampling
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
The Size of the Giant Component of a Random Graph with a Given Degree Sequence
Combinatorics, Probability and Computing
On the power-law random graph model of massive data networks
Performance Evaluation - Internet performance symposium (IPS 2002)
Bipartite structure of all complex networks
Information Processing Letters
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
Evolution and Structure of the Internet: A Statistical Physics Approach
Evolution and Structure of the Internet: A Statistical Physics Approach
Internet core topology mapping and analysis
Computer Communications
Bipartite graphs as models of complex networks
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
IEEE Journal on Selected Areas in Communications
On the bias of traceroute sampling: Or, power-law degree distributions in regular graphs
Journal of the ACM (JACM)
Mobile IPv6 deployments: Graph-based analysis and practical guidelines
Computer Communications
A recursive distributed topology discovery service for grid clients
IEEE Communications Letters
Bias reduction in traceroute sampling - towards a more accurate map of the internet
WAW'07 Proceedings of the 5th international conference on Algorithms and models for the web-graph
A logic distance-based method for deploying probing sources in the topology discovery
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
A recursive distributed topology discovery service for network-aware grid clients
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Evaluation of a new method for measuring the internet degree distribution: Simulation results
Computer Communications
Impact of sources and destinations on the observed properties of the internet topology
Computer Communications
K-core-preferred attack to the internet: is it more malicious than degree attack?
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
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Internet maps are generally constructed using the traceroute tool from a few sources to many destinations. It appeared recently that this exploration process gives a partial and biased view of the real topology, which leads to the idea of increasing the number of sources to improve the quality of the maps. In this paper, we present a set of experiments we have conducted to evaluate the relevance of this approach. It appears that the statistical properties of the underlying network have a strong influence on the quality of the obtained maps, which can be improved using massively distributed explorations. Conversely, some statistical properties are very robust, and so the known values for the Internet may be considered as reliable. We validate our analysis using real-world data and experiments, and we discuss its implications.