A Model Interpolating Between Regular And Scale Free Network With Tunable Exponent

Abstract - The purpose of this paper is to investigate a simple network model whereby a new node is either attached to the youngest of the existing node with probability p or it is attached with probability 1 - p to any of the existing node following the preferential attachment rule. For 0268804p1 the model exhibits power law degree distribution Pkk-26947 with 269473p2682601-p. The model thus nicely interpolates between the regular graph at p 1 with Pk26948k-2 and the Barabsi-Albert model at p 0 with Pkk-3.