Abstract
The study of complex networks is usually based on samples of the network. We analyze edge and node samples of dense homogeneous networks, obtained by shortest-path exploration of the network between a set of agents, distributed uniformly among the nodes. We characterize the density of the network by a novel metric based on the scaling of the average degree with the size of the network and present the edge and node sampling probability as a function of the agent density for the densest network scenarios.