1,808 research outputs found
Random Regular Graphs are not Asymptotically Gromov Hyperbolic
In this paper we prove that random --regular graphs with have
traffic congestion of the order where is the number
of nodes and geodesic routing is used. We also show that these graphs are not
asymptotically --hyperbolic for any non--negative almost
surely as .Comment: 6 pages, 2 figure
Scaling of Congestion in Small World Networks
In this report we show that in a planar exponentially growing network
consisting of nodes, congestion scales as independently of
how flows may be routed. This is in contrast to the 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 , for arbitrarily small . 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.Comment: 8 page
Traffic Analysis in Random Delaunay Tessellations and Other Graphs
In this work we study the degree distribution, the maximum vertex and edge
flow in non-uniform random Delaunay triangulations when geodesic routing is
used. We also investigate the vertex and edge flow in Erd\"os-Renyi random
graphs, geometric random graphs, expanders and random -regular graphs.
Moreover we show that adding a random matching to the original graph can
considerably reduced the maximum vertex flow.Comment: Submitted to the Journal of Discrete Computational Geometr
Lack of Hyperbolicity in Asymptotic Erd\"os--Renyi Sparse Random Graphs
In this work we prove that the giant component of the Erd\"os--Renyi random
graph for c a constant greater than 1 (sparse regime), is not Gromov
-hyperbolic for any positive with probability tending to one
as . As a corollary we provide an alternative proof that the giant
component of when c>1 has zero spectral gap almost surely as
.Comment: Updated version with improved results and narrativ
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