35 research outputs found

    Scaling of Congestion in Small World Networks

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    In this report we show that in a planar exponentially growing network consisting of NN nodes, congestion scales as O(N2/log(N))O(N^2/\log(N)) independently of how flows may be routed. This is in contrast to the O(N3/2)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(N1+ϵ)O(N^{1+\epsilon}), for arbitrarily small ϵ\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.Comment: 8 page

    Lack of Hyperbolicity in Asymptotic Erd\"os--Renyi Sparse Random Graphs

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    In this work we prove that the giant component of the Erd\"os--Renyi random graph G(n,c/n)G(n,c/n) for c a constant greater than 1 (sparse regime), is not Gromov δ\delta-hyperbolic for any positive δ\delta with probability tending to one as nn\to\infty. As a corollary we provide an alternative proof that the giant component of G(n,c/n)G(n,c/n) when c>1 has zero spectral gap almost surely as nn\to\infty.Comment: Updated version with improved results and narrativ
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