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.
This work was carried out when Antonio Lima was at the DIEEI, University of Catania.
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Mangioni, G., Lima, A. (2013). A Growing Model for Scale–Free Networks Embedded in Hyperbolic Metric Spaces. In: Menezes, R., Evsukoff, A., González, M. (eds) Complex Networks. Studies in Computational Intelligence, vol 424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30287-9_2
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DOI: https://doi.org/10.1007/978-3-642-30287-9_2
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