Organization of Growing Random Networks

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Abstract
The organizational development of growing random networks is investigated. These growing networks are built by adding nodes successively and linking each to an earlier node of degree k with attachment probability A_k. When A_k grows slower than linearly with k, the number of nodes with k links, N_k(t), decays faster than a power-law in k, while for A_k growing faster than linearly in k, a single node emerges which connects to nearly all other nodes. When A_k is asymptotically linear, N_k(t) tk^{-nu}, with nu dependent on details of the attachment probability, but in the range 2<nu<infty. The combined age and degree distribution of nodes shows that old nodes typically have a large degree. There is also a significant correlation in the degrees of neighboring nodes, so that nodes of similar degree are more likely to be connected. The size distributions of the in-components and out-components of the network with respect to a given node -- namely, its "descendants" and "ancestors" -- are also determined. The in-component exhibits a robust s^{-2} power-law tail, where s is the component size. The out component has a typical size of order ln t and it provides basic insights about the genealogy of the network.

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