A comprehensive weighted evolving network model

Abstract

Many social, technological, biological, and economical systems are best described by weighted networks, whose properties and dynamics depend not only on their structures but also on the connection weights among their nodes. However, most existing research work on complex network models are concentrated on network structures, with connection weights among their nodes being either 1 or 0. In this paper, we propose a new weighted evolving network model. Numerical simulations indicate that this network model yields three power-law distributions of the node degrees, connection weights and node strengths. Particularly, some other properties of the distributions, such as the droop-head and heavy-tail effects, can also be reflected by this model.

6 pages, 4 figures, accepted by Physica A

References in corpus (5)

• The structure and function of complex networks
• The architecture of complex weighted networks
• Weighted evolving networks: coupling topology and weights dynamics
• Weighted Scale-Free Networks with Stochastic Weight Assignments
• Nonextensive information entropy for stochastic networks

Cited by in corpus (5)

• Maximal planar networks with large clustering coefficient and power-law degree distribution
• An evolving network model with community structure
• A Mutual Selection Model for Weighted Networks
• Minimal models of weighted scale-free networks
• The origin of preferential attachment and the generalized preferential attachment for weighted networks