Scaling of Congestion in Small World Networks

Mathematics – Metric Geometry

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

8 pages

Scientific paper

In this report we show that in a planar exponentially growing network consisting of $N$ nodes, congestion scales as $O(N^2/\log(N))$ independently of how flows may be routed. This is in contrast to the $O(N^{3/2})$ scaling of congestion in a flat polynomially growing network. We also show that without the planarity condition, congestion in a small world network could scale as low as $O(N^{1+\epsilon})$, for arbitrarily small $\epsilon$. These extreme results demonstrate that the small world property by itself cannot provide guidance on the level of congestion in a network and other characteristics are needed for better resolution. Finally, we investigate scaling of congestion under the geodesic flow, that is, when flows are routed on shortest paths based on a link metric. Here we prove that if the link weights are scaled by arbitrarily small or large multipliers then considerable changes in congestion may occur. However, if we constrain the link-weight multipliers to be bounded away from both zero and infinity, then variations in congestion due to such remetrization are negligible.

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

Scaling of Congestion in Small World 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 Scaling of Congestion in Small World Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Scaling of Congestion in Small World Networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-320930

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