Preferential attachment with partial information

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Résumé

We propose a preferential attachment model for network growth where new entering nodes have a partial information about the state of the network. Our main result is that the presence of bounded information modifies the degree distribution by introducing an exponential tail, while it preserves a
power law behaviour over a finite small range of degrees. On the other hand, unbounded information is sufficient to let the network grow as in the standard Barabási-Albert model. Surprisingly, the latter feature holds true also when the fraction of known nodes goes asymptotically to zero. Analytical
results are compared to direct simulations.
langue originaleAnglais
EditeurNamur center for complex systems
Nombre de pages6
Volume9
Edition14
Etat de la publicationPublié - 4 sept. 2014

Série de publications

NomnaXys Technical Report Series
EditeurUniversity of Namur
Numéro14
Volume9

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  • Projets

    PAI n°P7/19 - DYSCO: Dynamical systems, control and optimization (DYSCO)

    WINKIN, J., Blondel, V., Vandewalle, J., Pintelon, R., Sepulchre, R., Vande Wouwer, A. & SARTENAER, A.

    1/04/1230/09/17

    Projet: Recherche

    Contient cette citation

    Carletti, T., Gargiulo, F., & Lambiotte, R. (2014). Preferential attachment with partial information. (14 Ed.) (naXys Technical Report Series; Vol 9, Numéro 14). Namur center for complex systems.