3 results match your criteria: "CSIRO Centre for Complex System Science[Affiliation]"

We investigate networks whose evolution is governed by the interaction of a random assembly process and an optimization process. In the first process, new nodes are added one at a time and form connections to randomly selected old nodes. In between node additions, the network is rewired to minimize its path length.

View Article and Find Full Text PDF

Coordinated and uncoordinated optimization of networks.

Phys Rev E Stat Nonlin Soft Matter Phys

June 2010

CSIRO Marine and Atmospheric Research, CSIRO Centre for Complex System Science, F. C. Pye Laboratory, Canberra, Australian Capital Territory 2601, Australia.

In this paper, we consider spatial networks that realize a balance between an infrastructure cost (the cost of wire needed to connect the network in space) and communication efficiency, measured by average shortest path length. A global optimization procedure yields network topologies in which this balance is optimized. These are compared with network topologies generated by a competitive process in which each node strives to optimize its own cost-communication balance.

View Article and Find Full Text PDF

Optimal synchronization in space.

Phys Rev E Stat Nonlin Soft Matter Phys

February 2010

CSIRO Marine and Atmospheric Research, CSIRO Centre for Complex System Science, FC Pye Laboratory, G.P.O. Box 3023, Clunies Ross Street, Canberra, Australian Capital Territory 2601, Australia.

In this Rapid Communication we investigate spatially constrained networks that realize optimal synchronization properties. After arguing that spatial constraints can be imposed by limiting the amount of "wire" available to connect nodes distributed in space, we use numerical optimization methods to construct networks that realize different trade offs between optimal synchronization and spatial constraints. Over a large range of parameters such optimal networks are found to have a link length distribution characterized by power-law tails P(l) proportional to l(-alpha), with exponents alpha increasing as the networks become more constrained in space.

View Article and Find Full Text PDF