870 research outputs found
Optimal interdependence between networks for the evolution of cooperation
Recent research has identified interactions between networks as crucial for the outcome of evolutionary
games taking place on them. While the consensus is that interdependence does promote cooperation by
means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we
here address the question just how much interdependence there should be. Intuitively, one might assume
the more the better. However, we show that in fact only an intermediate density of sufficiently strong
interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate
interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links
between the networks, and the independent formation of cooperative patterns on each individual network.
Presented results are robust to variations of the strategy updating rule, the topology of interdependent
networks, and the governing social dilemma, thus suggesting a high degree of universality
Assortativity Decreases the Robustness of Interdependent Networks
It was recently recognized that interdependencies among different networks
can play a crucial role in triggering cascading failures and hence system-wide
disasters. A recent model shows how pairs of interdependent networks can
exhibit an abrupt percolation transition as failures accumulate. We report on
the effects of topology on failure propagation for a model system consisting of
two interdependent networks. We find that the internal node correlations in
each of the two interdependent networks significantly changes the critical
density of failures that triggers the total disruption of the two-network
system. Specifically, we find that the assortativity (i.e. the likelihood of
nodes with similar degree to be connected) within a single network decreases
the robustness of the entire system. The results of this study on the influence
of assortativity may provide insights into ways of improving the robustness of
network architecture, and thus enhances the level of protection of critical
infrastructures
Towards a Realistic Model for Failure Propagation in Interdependent Networks
Modern networks are becoming increasingly interdependent. As a prominent
example, the smart grid is an electrical grid controlled through a
communications network, which in turn is powered by the electrical grid. Such
interdependencies create new vulnerabilities and make these networks more
susceptible to failures. In particular, failures can easily spread across these
networks due to their interdependencies, possibly causing cascade effects with
a devastating impact on their functionalities.
In this paper we focus on the interdependence between the power grid and the
communications network, and propose a novel realistic model, HINT
(Heterogeneous Interdependent NeTworks), to study the evolution of cascading
failures. Our model takes into account the heterogeneity of such networks as
well as their complex interdependencies. We compare HINT with previously
proposed models both on synthetic and real network topologies. Experimental
results show that existing models oversimplify the failure evolution and
network functionality requirements, resulting in severe underestimations of the
cascading failures.Comment: 7 pages, 6 figures, to be published in conference proceedings of IEEE
International Conference on Computing, Networking and Communications (ICNC
2016), Kauai, US
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