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

Autor:	P. D. Arjona-Villicaña, P. Castillo Castillo, and J. Acosta-Elias
Rok vydání:	2019
Předmět:	business.industry Computer science General Physics and Astronomy Growth model Complex network Topology Network topology Education Accelerated Growth Range (mathematics) Distribution (mathematics) The Internet business Autonomous system (mathematics)
Zdroj:	Revista Mexicana de Física. 65:128-132
ISSN:	2683-2224 0035-001X
DOI:	10.31349/revmexfis.65.128
Popis:	Many real-life complex networks have in-degree and out-degree distributions that decay as apower-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 thesemodels is that they add links from nodes which are created into the network, as well as betweennodes already present in this network. However, adding links between existing nodes is not acharacteristic available in all systems. This paper introduces a new complex network growthmodel that, without adding links between existing nodes is able to generate complex topologieswith in-degree and out-degree distributions that decay as a power-law. Moreover, in this growthmodel, the ratio at which links are created is greater than the ratio at which nodes are born, whichproduces an accelerated growth phenomenon that can be found in some real systems, like theInternet at the Autonomous System level.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f4d1ae9f16936da238b3edc2a21d62b0 https://doi.org/10.31349/revmexfis.65.128 Zobrazit plný text záznamu