11,055 research outputs found
Optimal Path and Minimal Spanning Trees in Random Weighted Networks
We review results on the scaling of the optimal path length in random
networks with weighted links or nodes. In strong disorder we find that the
length of the optimal path increases dramatically compared to the known small
world result for the minimum distance. For Erd\H{o}s-R\'enyi (ER) and scale
free networks (SF), with parameter (), we find that the
small-world nature is destroyed. We also find numerically that for weak
disorder the length of the optimal path scales logaritmically with the size of
the networks studied. We also review the transition between the strong and weak
disorder regimes in the scaling properties of the length of the optimal path
for ER and SF networks and for a general distribution of weights, and suggest
that for any distribution of weigths, the distribution of optimal path lengths
has a universal form which is controlled by the scaling parameter
where plays the role of the disorder strength, and
is the length of the optimal path in strong disorder. The
relation for is derived analytically and supported by numerical
simulations. We then study the minimum spanning tree (MST) and show that it is
composed of percolation clusters, which we regard as "super-nodes", connected
by a scale-free tree. We furthermore show that the MST can be partitioned into
two distinct components. One component the {\it superhighways}, for which the
nodes with high centrality dominate, corresponds to the largest cluster at the
percolation threshold which is a subset of the MST. In the other component,
{\it roads}, low centrality nodes dominate. We demonstrate the significance
identifying the superhighways by showing that one can improve significantly the
global transport by improving a very small fraction of the network.Comment: review, accepted at IJB
Optimal Traffic Networks
Inspired by studies on the airports' network and the physical Internet, we
propose a general model of weighted networks via an optimization principle. The
topology of the optimal network turns out to be a spanning tree that minimizes
a combination of topological and metric quantities. It is characterized by a
strongly heterogeneous traffic, non-trivial correlations between distance and
traffic and a broadly distributed centrality. A clear spatial hierarchical
organization, with local hubs distributing traffic in smaller regions, emerges
as a result of the optimization. Varying the parameters of the cost function,
different classes of trees are recovered, including in particular the minimum
spanning tree and the shortest path tree. These results suggest that a
variational approach represents an alternative and possibly very meaningful
path to the study of the structure of complex weighted networks.Comment: 4 pages, 4 figures, final revised versio
Distributed Approximation of Minimum Routing Cost Trees
We study the NP-hard problem of approximating a Minimum Routing Cost Spanning
Tree in the message passing model with limited bandwidth (CONGEST model). In
this problem one tries to find a spanning tree of a graph over nodes
that minimizes the sum of distances between all pairs of nodes. In the
considered model every node can transmit a different (but short) message to
each of its neighbors in each synchronous round. We provide a randomized
-approximation with runtime for
unweighted graphs. Here, is the diameter of . This improves over both,
the (expected) approximation factor and the runtime
of the best previously known algorithm.
Due to stating our results in a very general way, we also derive an (optimal)
runtime of when considering -approximations as done by the
best previously known algorithm. In addition we derive a deterministic
-approximation
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