27 research outputs found
Distributed flow optimization and cascading effects in weighted complex networks
We investigate the effect of a specific edge weighting scheme on distributed flow efficiency and robustness to cascading
failures in scale-free networks. In particular, we analyze a simple, yet
fundamental distributed flow model: current flow in random resistor networks.
By the tuning of control parameter and by considering two general cases
of relative node processing capabilities as well as the effect of bandwidth, we
show the dependence of transport efficiency upon the correlations between the
topology and weights. By studying the severity of cascades for different
control parameter , we find that network resilience to cascading
overloads and network throughput is optimal for the same value of over
the range of node capacities and available bandwidth
Modern temporal network theory: A colloquium
The power of any kind of network approach lies in the ability to simplify a
complex system so that one can better understand its function as a whole.
Sometimes it is beneficial, however, to include more information than in a
simple graph of only nodes and links. Adding information about times of
interactions can make predictions and mechanistic understanding more accurate.
The drawback, however, is that there are not so many methods available, partly
because temporal networks is a relatively young field, partly because it more
difficult to develop such methods compared to for static networks. In this
colloquium, we review the methods to analyze and model temporal networks and
processes taking place on them, focusing mainly on the last three years. This
includes the spreading of infectious disease, opinions, rumors, in social
networks; information packets in computer networks; various types of signaling
in biology, and more. We also discuss future directions.Comment: Final accepted versio