Optimal network topologies for local search with congestion

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

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4 pages. Final version accepted in PRL

Scientific paper

10.1103/PhysRevLett.89.248701

The problem of searchability in decentralized complex networks is of great importance in computer science, economy and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion effects that arise when parallel searches are performed, and obtain expressions for the average search cost--written in terms of the search algorithm and the topological properties of the network--both in presence and abscence of congestion. This formalism is used to obtain optimal network structures for a system using a local search algorithm. It is found that only two classes of networks can be optimal: star-like configurations, when the number of parallel searches is small, and homogeneous-isotropic configurations, when the number of parallel searches is large.

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