Evolution of two properties for scale-free network

1 .INTRODUCTIONBecause complex network structure can describe awide variety of systems of high technological andintellectual i mportance ,there has been a consider-able interest in the growth properties of randomnetworks1 ,2]. The typical random network is ascale-free network, which connectivity distribu-tions behave as power law. Scale-free network isan evolving network, which has many propertiesduring evolution, for example , the fitness andclustering coefficient of node are two i mport…

Evolution of two properties for scale-free network

Fitness of node can denote its competing power and clustering denotes the transitivity of network. Because the fitness of node is uncertain or fuzzy in some social networks, an explicit form of the degree distribution on fuzzy fitness is derived within a mean field approach. It is a weighted sum of different fuzzy fitness. It can be found that the fuzzy fitness of nodes may lead to multiscaling. Moreover, the clustering coefficient of node decays as power law and clustering coefficient of network behavior not-decrease-but-increase' phenomenon after some time. Some computer simulation results of these models illustrate these analytical results.