by Baccelli and Zuyev [@baccelliZuyev]. However, the network structure investigated in that paper is obtained by iteratively considering Voronoi tessellations and does not exhibit fractal geometries (see however [@aggTess] for some results in this direction).

In order to develop a fundamental understanding of the asymptotic behavior of cable lengths and chemical distances (i.e., minimal number of hops needed to connect two points) in large networks, it is important to abstract from the types of specific countries and deterministic fractals investigated in [@aby1; @koski] and move to random networks. The spatial nature of the problem calls for models based on random geometric graphs, and the fractal geometry suggests that one should look for scale-free random graphs exhibiting a power-law degree distribution. The combination of these two constraints restricts the list of appropriate choices substantially. We briefly review some of the most well-known models in literature and discuss their drawbacks with respect to modeling the kind of networks we have in mind.

One option could be to use long-range percolation, see [@lrp1; @lrp2; @copper] and the references therein. Here, one starts from the lattice $\Z^d$ and connects any pair of sites independently with a probability depending only on their distance. This leads 