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Artículo

K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases

Alvarez Hamelin, José IgnacioIcon ; Dall'Asta, Luca; Barrat, Alain; Vespignani, Alessandro
Fecha de publicación: 06/2008
Editorial: American Institute of Mathematical Sciences
Revista: Networks and Heterogeneous Media
ISSN: 1556-1801
Idioma: Inglés
Tipo de recurso: Artículo publicado

Resumen

We consider the k-core decomposition of network models and Internet graphs at the autonomous system (AS) level. The k-core analysis allows to characterize networks beyond the degree distribution and uncover structural properties and hierarchies due to the specific architecture of the system. We compare the k-core structure obtained for AS graphs with those of several network models and discuss the differences and similarities with the real Internet architecture. The presence of biases and the incompleteness of the real maps are discussed and their effect on the k-core analysis is assessed with numerical experiments simulating biased exploration on a wide range of network models. We find that the k-core analysis provides an interesting characterization of the fluctuations and incompleteness of maps as well as information helping to discriminate the original underlying structure.
Palabras clave: K-Core Decomposition , Internet Maps
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/20126
URL: http://www.aimsciences.org/journals/displayArticles.jsp?paperID=3285
URL: https://arxiv.org/abs/cs/0511007
DOI: http://dx.doi.org/10.3934/nhm.2008.3.371
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Articulos(INTECIN)
Articulos de INST.D/TEC.Y CS.DE LA ING."HILARIO FERNANDEZ LONG"
Citación
Alvarez Hamelin, José Ignacio; Dall'Asta, Luca; Barrat, Alain; Vespignani, Alessandro; K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases; American Institute of Mathematical Sciences; Networks and Heterogeneous Media; 3; 2; 6-2008; 371-393
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