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Optimal spatial transportation networks where link costs are sublinear in link capacity

D J Aldous

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Consider designing a transportation network on n vertices in the plane, with traffic demand uniform over all source–destination pairs. Suppose the cost of a link of length \ell and capacity c scales as \ell c^{\beta } for fixed 0<β<1. Under appropriate standardization, the cost of the minimum cost Gilbert network grows essentially as nα(β), where α(β) = 1−(β/2) on 0 \lt \beta \leq \frac {1}{2} and \alpha (\beta)=\frac {1}{2}+({\beta }/{2}) on \frac {1}{2} \leq \beta \lt 1 . This quantity is an upper bound in the worst case (of vertex positions) and a lower bound under mild regularity assumptions. Essentially the same bounds hold if we constrain the network to be efficient in the sense that average route length is only 1+o(1) times the average straight line length. The transition at \beta=\frac {1}{2} corresponds to the dominant cost contribution changing from short links to long links. The upper bounds arise in the following type of hierarchical networks, which are therefore optimal in an order-of-magnitude sense. On the large scale, we use a sparse Poisson line process to provide long-range links. On the medium scale, we use hierarchical routing on the square lattice. On the small scale, we link vertices directly to medium-grid points. We discuss one of the many possible variant models, in which links also have a designed maximum speed s and the cost becomes \ell c^{\beta } s^{\gamma } .


Keywords

random graphs, networks

traffic models

communication, supply and information networks

PACS

89.40.Dd Air transporation

89.75.Hc Networks and genealogical trees

02.10.Ox Combinatorics; graph theory

05.40.-a Fluctuation phenomena, random processes, noise, and Brownian motion

MSC

91B32 Resource and cost allocation

90B15 Network models, stochastic

90B20 Traffic problems

82B20 Lattice systems (Ising, dimer, Potts, etc.) and systems on graphs

05C80 Random graphs

Subjects

Mathematical physics

Environmental and Earth science

Statistical physics and nonlinear systems

Dates

Issue 03 (March 2008)

Received 30 January 2008, accepted for publication 20 February 2008

Published 11 March 2008



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