A minimal model for congestion phenomena on complex networks

Physics – Condensed Matter – Statistical Mechanics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We study a minimal model of traffic flows in complex networks, simple enough to get analytical results, but with a very rich phenomenology, presenting continuous, discontinuous as well as hybrid phase transitions between a free-flow phase and a congested phase, critical points and different scaling behaviors in the system size. It consists of random walkers on a queueing network with one-range repulsion, where particles can be destroyed only if they can move. We focus on the dependence on the topology as well as on the level of traffic control. We are able to obtain transition curves and phase diagrams at analytical level for the ensemble of uncorrelated networks and numerically for single instances. We find that traffic control improves global performance, enlarging the free-flow region in parameter space only in heterogeneous networks. Traffic control introduces non-linear effects and, beyond a critical strength, may trigger the appearance of a congested phase in a discontinuous manner. The model also reproduces the cross-over in the scaling of traffic fluctuations empirically observed in the Internet, and moreover, a conserved version can reproduce qualitatively some stylized facts of traffic in transportation networks.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A minimal model for congestion phenomena on complex networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A minimal model for congestion phenomena on complex networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A minimal model for congestion phenomena on complex networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-495173

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.