Growing networks with temporal effect and mixed attachment mechanisms

In this paper, motivated by previous research works on the evolution of the network topology, i.e., the combination of preferential attachment and temporal effect (aging of vertices), we propose a novel model which combines the mixed attachment mechanisms (preferential attachment and uniform attachment) and the temporal effect to investigate the topological properties of the network during the evolution. Our results show that the degree distribution of the model follows the exponential-decaying form.