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. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Mangioni, G., & Lima, A. (2013). A growing model for scale-free networks embedded in hyperbolic metric spaces. In Studies in Computational Intelligence (Vol. 424, pp. 9–17). Springer Verlag. https://doi.org/10.1007/978-3-642-30287-9_2
Mendeley helps you to discover research relevant for your work.