Generating clustered scale-free networks using Poisson based localization of edges


PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, cilt.497, ss.72-85, 2018 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 497
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.physa.2018.01.009
  • Sayfa Sayıları: ss.72-85


We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach. (C) 2018 Elsevier B.V. All rights reserved.