Abstract In this paper we devise a generative random network model with core–periphery properties whose core nodes act as sublinear dominators , that is, if the has n nodes, size o ( ) and dominates entire network. We show instances generated by exhibit power law degree distributions, incorporates small-world phenomena. also fit our in variety of real-world networks.