  Real complex networks are often characterized by spatial constraints such as
the relative position and adjacency of nodes. The present work describes how
Voronoi tessellations of the space where the network is embedded provide not
only a natural means for relating such networks with metric spaces, but also a
natural means for obtaining fractal complex networks. A series of comprehensive
measurements closely related to spatial aspects of these networks is proposed,
which includes the effective length, adjacency, as well as the fractal
dimension of the network in terms of the spatial scales defined by successive
shortest paths starting from a specific node. The potential of such features is
illustrated with respect to the random, small-world, scale-free and fractal
network models.
