Turker, Ilker2024-09-292024-09-2920180378-43711873-2119https://doi.org/10.1016/j.physa.2018.01.009https://hdl.handle.net/20.500.14619/5195We 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.eninfo:eu-repo/semantics/closedAccessNetwork modelingClusteringScale-free networksSmall-world networksArticle10.1016/j.physa.2018.01.0092-s2.0-8504286632785Q272497WOS:000428826700007Q2