M. Song and S. Shetty (USA)
Scale-free networks, modeling, power-law distribution, evolutionary.
The study of scale-free networks typically assumes that either nodes are homogenously distributed or one strong node monopolizes the entire network. While this makes the analysis trackable, it is not appropriate for scenarios, such as terrorist networks, in which nodes play significant different roles in the network. In this paper, we classify nodes into four types by the roles they play. Nodes from different types are assigned various fitness values. The presence of varied fitness values influences the probability of a node to receive preferentially links from other nodes. Thus our model involves simultaneous interaction between nodes of varied strengths. Although the model allocates the same fitness strength to all nodes of the same type, analytical results suggest that it is sufficient to demonstrate the two key features of scale free networks: power-law distribution of degree and preferential attachment of new nodes. Simulations are performed to verify the proposed model.
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