General random pseudofractal networks

We introduce a general random pseudofractal network model by assigning fitness to each edge. In this model, continuous growth and attachment, determined by their fitness of already existing edges, are the two ingredients. We obtain the analytical results that our model exhibits a power-law degree distribution with exponent γ = 2 + m(1 + αm)^-1, where m and α are tunable parameters. We also show that a general random pseudofractal network has a large clustering coefficient and a small average distance leading to a small-world effect. These theoretical results agree well with numerical simulations.