Structure properties of evolutionary spatially embedded networks

Z. Hui, W. Li, X. Cai, J.M. Greneche and Q.A. Wang

Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, issue 8, 1909-1919

Abstract: This work is a modeling of evolutionary networks embedded in one or two dimensional configuration space. The evolution is based on two attachments depending on degree and spatial distance. The probability for a new node n to connect with a previous node i at distance rni follows aki∑jkj+(1−a)rni−α∑jrnj−α, where ki is the degree of node i, α and a are tunable parameters. In spatial driven model (a=0), the spatial distance distribution follows the power-law feature. The mean topological distance l and the clustering coefficient C exhibit phase transitions at same critical values of α which change with the dimensionality d of the embedding space. When a≠0, the degree distribution follows the “shifted power law” (SPL) which interpolates between exponential and scale-free distributions depending on the value of a.

Keywords: Euclidean distance preference; Small world network; Phase transition; Master equation method; Mean-field approximation (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:392:y:2013:i:8:p:1909-1919

DOI: 10.1016/j.physa.2013.01.002

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