Transport is an important function in many network systems and understanding
its behavior on biological, social, and technological networks is crucial for a
wide range of applications. However, it is a property that is not
well-understood in these systems and this is probably due to the lack of a
general theoretical framework. Here, based on the finding that renormalization
can be applied to bio-networks, we develop a scaling theory of transport in
self-similar networks. We demonstrate the networks invariance under length
scale renormalization and we show that the problem of transport can be
characterized in terms of a set of critical exponents. The scaling theory
allows us to determine the influence of the modular structure on transport. We
also generalize our theory by presenting and verifying scaling arguments for
the dependence of transport on microscopic features, such as the degree of the
nodes and the distance between them. Using transport concepts such as diffusion
and resistance we exploit this invariance and we are able to explain, based on
the topology of the network, recent experimental results on the broad flow
distribution in metabolic networks.Comment: 8 pages, 6 figure