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Deciding on the type of the degree distribution of a graph from traceroute-like measurements

Xiaomin Wang, Matthieu Latapy, Michèle Soria

International Journal of Computer Networks & Communications (IJCNC), May 2012, Volume 4. Number 3

The degree distribution of the Internet topology is considered as one of its main properties. However, it is only known through a measurement procedure which gives a biased estimate. This measurement may in first approximation be modeled by a BFS (Breadth-First Search) tree. We explore here our ability to infer the type (Poisson or power-law) of the degree distribution from such a limited knowledge. We design procedures which estimate the degree distribution of a graph from a BFS of it, and show experimentally (on models and real-world data) that this approach succeeds in making the difference between Poisson and power-law degree distributions.

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A Real-World Spreading Experiment in the Blogosphere

Adrien Friggeri, Jean-Philippe Cointet and Matthieu Latapy

Complex Systems 19, 2011

We designed an experiment to observe a spreading phenomenon in the blogosphere. This experiment relies on a small applet that participants copy on their own web page. We present the obtained dataset, which we freely provide for study, and conduct basic analysis. We conclude that, despite the classical assumption, in this experiment famous blogs do not necessarily act as super spreaders.

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A Radar for the Internet

Matthieu Latapy, Clémence Magnien and Frédéric Ouédraogo

Complex Systems, 20 (1), 23-30, 2011.

Mapping the internet’s topology is a challenge in itself, and studying its dynamics is even more difficult. Achieving this would however provide key information on the nature of the internet, crucial for modeling and simulation. Moreover, detecting anomalies in this dynamics is a key issue for security. We introduce here a new measurement approach which makes it possible to capture internet dynamics at a scale of a few minutes in a radar-like manner. By conducting and analyzing large-scale measurements of this kind, we rigorously and automatically detect events in the observed dynamics, which is totally out of reach of previous approaches.

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Ten weeks in the life of an eDonkey server

Frédéric Aidouni, Matthieu Latapy and Clémence Magnien

Sixth International Workshop on Hot Topics in Peer-to-Peer Systems (Hot-P2P 2009), May 29, 2009, Rome, Italy

This paper presents a capture of the queries managed by an eDonkey server during almost 10 weeks, leading to the observation of almost 9 billion messages involving almost 90 million users and more than 275 million distinct files. Acquisition and management of such data raises several challenges, which we discuss as well as the solutions we developed. We obtain a very rich dataset, orders of magnitude larger than previously avalaible ones, which we provide for public use. We finally present basic analysis of the obtained data, which already gives evidence of non-trivial features.

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Measurement of eDonkey Activity with Distributed Honeypots

Oussama Allali, Matthieu Latapy and Clémence Magnien

Sixth International Workshop on Hot Topics in Peer-to-Peer Systems (Hot-P2P 2009), May 29, 2009, Rome, Italy

Collecting information about user activity in peer-to-peer systems is a key but challenging task. We describe here a distributed platform for doing so on the eDonkey network, relying on a group of honeypot peers which claim to have certain files and log queries they receive for these files. We then conduct some measurements with typical scenarios and use the obtained data to analyze the impact of key parameters like measurement duration, number of honeypots involved, and number of advertised files. This illustrates both the possible uses of our measurement system, and the kind of data one may collect using it.

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A Radar for the Internet

Matthieu Latapy, Clémence Magnien and Frédéric Ouédraogo

Proceedings of ADN’08: 1st International Workshop on Analysis of Dynamic Networks, in conjunction with IEEE ICDM 2008

In contrast with most internet topology measurement research, our concern here is not to obtain a map as complete and precise as possible of the whole internet. Instead, we claim that each machine’s view of this topology, which we call ego-centered view, is an object worth of study in itself. We design and implement an ego-centered measurement tool, and perform radar-like measurements consisting of repeated measurements of such views of the internet topology. We conduct long-term (several weeks) and high-speed (one round every few minutes) measurements of this kind from more than one hundred monitors, and we provide the obtained data. We also show that these data may be used to detect events in the dynamics of internet topology.

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