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A Growing Model for Scale–Free Networks Embedded in Hyperbolic Metric Spaces

  • Giuseppe Mangioni
  • Antonio Lima
Part of the Studies in Computational Intelligence book series (SCI, volume 424)

Abstract

Some results by Krioukov et al. show how real world networks are produced by hidden metric spaces. Specifically, scale-free networks can be obtained from hyperbolic metric spaces. While the model proposed by Krioukov can produce a static scale-free network, all nodes are created at one time and none can be later added. In this work we propose a growing model which leverages the same concepts and allows to gradually add nodes to a scale-free network, obtained from a discretised hyperbolic model. We also show how nodes are correctly positioned relying on local information and how greedy routing builds optimal paths in the network.

Keywords

Degree Distribution Hyperbolic Space Ideal Point Overlay Network Average Path Length 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.DIEEIUniversity of CataniaCataniaItaly
  2. 2.School of Computer ScienceUniversity of BirminghamEdgbastonUnited Kingdom

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