Entropy Rate of Diffusion Processes on Complex Networks

Abstract

The concept of entropy rate for a dynamical process on a graph is introduced. We study diffusion processes where the node degrees are used as a local information by the random walkers. We describe analitically and numerically how the degree heterogeneity and correlations affect the diffusion entropy rate. In addition, the entropy rate is used to characterize complex networks from the real world. Our results point out how to design optimal diffusion processes that maximize the entropy for a given network structure, providing a new theoretical tool with applications to social, technological and communication networks.

4 pages (APS format), 3 figures, 1 table

References in corpus (7)

• Maps of random walks on complex networks reveal community structure
• Reaction-diffusion processes and metapopulation models in heterogeneous networks
• Networks and Cities: An Information Perspective
• The entropy of randomized network ensembles
• Information Horizons in Networks
• Correlations between structure and dynamics in complex networks
• Optimization and Scale-freeness for Complex Networks

Cited by in corpus (1)

• The entropy of network ensembles