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Structure properties of evolutionary spatially embedded networks

Author

Listed:
  • Hui, Z.
  • Li, W.
  • Cai, X.
  • Greneche, J.M.
  • Wang, Q.A.

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.

Suggested Citation

  • Hui, Z. & Li, W. & Cai, X. & Greneche, J.M. & Wang, Q.A., 2013. "Structure properties of evolutionary spatially embedded networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1909-1919.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:8:p:1909-1919
    DOI: 10.1016/j.physa.2013.01.002
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