Modeling the evolution of weighted networks.

By Alain Barrat, Marc Barthelemy, Alessandro Vespignani. Physical review. E, Statistical, nonlinear, and soft matter physics, 2004

305 citations recorded by the source corpus.

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement mechanism coupled to the local network growth. That coupling can be generalized in order to include the effect of additional randomness and nonlinearities which can be present in real-world networks. The model generates weighted graphs exhibiting the statistical properties observed in several real-world systems. In particular, the model yields a nontrivial time evolution of vertices' properties and scale-free behavior with exponents depending on the microscopic parameters characterizing the coupling rules. Very interestingly, the generated graphs spontaneously achieve a complex hierarchical architecture characterized by clustering and connectivity correlations varying as a function of the vertices' degree.

Subfields: Condensed Matter Physics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/7c87b6710b65a62b86a69624e3b6c0206ed6a086

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Citations in the corpus

• An Energy-Balanced Routing Method Based on Forward-Aware Factor for Wireless Sensor Networks (2014, methodology): “BASIC BBV WEIGHTED NETWORK MODEL AND LOCAL-WORLD THEORY Based on our research work, we know the topology evolving of BBV model can be divided into four stages as follows [20].”