16,384 research outputs found
Biased random walks on complex networks: the role of local navigation rules
We study the biased random walk process in random uncorrelated networks with
arbitrary degree distributions. In our model, the bias is defined by the
preferential transition probability, which, in recent years, has been commonly
used to study efficiency of different routing protocols in communication
networks. We derive exact expressions for the stationary occupation
probability, and for the mean transit time between two nodes. The effect of the
cyclic search on transit times is also explored. Results presented in this
paper give the basis for theoretical treatment of the transport-related
problems on complex networks, including quantitative estimation of the critical
value of the packet generation rate.Comment: 5 pages (Phys. Rev style), 3 Figure
Flow graphs: interweaving dynamics and structure
The behavior of complex systems is determined not only by the topological
organization of their interconnections but also by the dynamical processes
taking place among their constituents. A faithful modeling of the dynamics is
essential because different dynamical processes may be affected very
differently by network topology. A full characterization of such systems thus
requires a formalization that encompasses both aspects simultaneously, rather
than relying only on the topological adjacency matrix. To achieve this, we
introduce the concept of flow graphs, namely weighted networks where dynamical
flows are embedded into the link weights. Flow graphs provide an integrated
representation of the structure and dynamics of the system, which can then be
analyzed with standard tools from network theory. Conversely, a structural
network feature of our choice can also be used as the basis for the
construction of a flow graph that will then encompass a dynamics biased by such
a feature. We illustrate the ideas by focusing on the mathematical properties
of generic linear processes on complex networks that can be represented as
biased random walks and also explore their dual consensus dynamics.Comment: 4 pages, 1 figur
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