Jean-Loup Guillaume, Matthieu Latapy and Stevens Le-Blond
LNCS, proceedings of the 6-th International Workshop on Distributed Computing IWDC’04, 2004, Kolkata, India
Despite their crucial impact on the performances of P2P systems,
very few is known on peers behaviors in such networks. We propose
here a study of these behaviors in a running environment using a semicentralised
P2P system (eDonkey). To achieve this, we use a trace of the
queries made to a large server managing up to fifty thousands peers simultaneously,
and a few thousands queries per second. We analyse these
data using complex network methods, and focus in particular on the degrees,
their correlations, and their time-evolution. Results show a large
variety of observed phenomena, including the variety of peers behaviors
and heterogeneity of data queries, which should be taken into account
when designing P2P systems.
Jean-Loup Guillaume and Matthieu Latapy
Information Processing Letters (IPL) 90:5, pages 215-221, 2004
The analysis and modelling of various complex networks has received much attention in the last few years. Some such networks display a natural bipartite structure: two kinds of nodes coexist with links only between nodes of different kinds. This bipartite structure has not been deeply studied until now, mainly because it appeared to be specific to only a few complex networks. However, we show here that all complex networks can be viewed as bipartite structures sharing some important statistics, like degree distributions. The basic properties of complex networks can be viewed as consequences of this underlying bipartite structure. This leads us to propose the first simple and intuitive model for complex networks which captures the main properties met in practice.
Jean-Loup Guillaume, Matthieu Latapy and Laurent Viennot
LNCS, proceedings of the 3-rd international conference Web-Age Information Management WAIM’02, 2002, Beijing, Chine. Abstract published in the proceedings of the 11-th international conference World Wide Web WWW’02, 2002, Honolulu, Hawaï
In this paper, we propose a set of simple and efficient methods based on standard, free and widely available tools, to store and manipulate large sets of URLs and large parts of the Web graph. Our aim is both to store efficiently the URLs list and the graph in order to manage all the computations in a computer central memory. We also want to make the conversion between URLs and their identifiers as fast as possible, and to obtain all the successors of an URL in the Web graph efficiently. The methods we propose make it possible to obtain a good compromise between these two challenges, and make it possible to manipulate large parts of the Web graph.