Extreme fluctuations in noisy task-completion landscapes on scale-free networks

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We study the statistics and scaling of extreme fluctuations in noisy task-completion landscapes, such as those emerging in synchronized distributed-computing networks, or generic causally-constrained queuing networks, with scale-free topology. In these networks the average size of the fluctuations becomes finite (synchronized state) and the extreme fluctuations typically diverge only logarithmically in the large system-size limit ensuring synchronization in a practical sense. Provided that local fluctuations in the network are short-tailed, the statistics of the extremes are governed by the Gumbel distribution. We present large-scale simulation results using the exact algorithmic rules, supported by mean-field arguments based on a coarse-grained description.
16 pages, 6 figures, revtex

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Disordered Systems and Neural Networks, Statistical Mechanics

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http://salesiana.dossiersoluciones.com/handle/123456789/137400

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cond-mat/0701301
 http://arxiv.org/abs/cond-mat/0701301
 Chaos 17, 026104 (2007)
 doi:10.1063/1.2735446

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arXiv