An accelerated growth model to generate complex networks with connectivity distribution slope that varies with time

P. Castillo Castillo, P.D. Arjona-Villicaña, and J. Acosta-Elias

Abstract


Many real-life complex networks have in-degree and out-degree distributions that decay as a
power-law. However, the few models that have been able to reproduce both of these properties,
cannot reproduce the wide range of values found in real systems. Another limitation of these
models is that they add links from nodes which are created into the network, as well as between
nodes already present in this network. However, adding links between existing nodes is not a
characteristic available in all systems. This paper introduces a new complex network growth
model that, without adding links between existing nodes is able to generate complex topologies
with in-degree and out-degree distributions that decay as a power-law. Moreover, in this growth
model, the ratio at which links are created is greater than the ratio at which nodes are born, which
produces an accelerated growth phenomenon that can be found in some real systems, like the
Internet at the Autonomous System level.


Keywords


Complex networks, scale-free networks, Barabási model, Krapivsky-Redner model.

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DOI: https://doi.org/10.31349/RevMexFis.65.128

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Revista Mexicana de Física

ISSN: 0035-001X

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