Using relaxational dynamics to reduce network congestion

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dc.creatorPiontti, A. L. Pastore Y
dc.creatorLa Rocca, C. E.
dc.creatorToroczkai, Z.
dc.creatorBraunstein, L. A.
dc.creatorMacri, P. A.
dc.creatorLopez, E.
dc.date2008-03-26
dc.date.accessioned2026-07-07T09:28:39Z
dc.date.available2026-07-07T09:28:39Z
dc.descriptionWe study the effects of relaxational dynamics on congestion pressure in scale free networks by analyzing the properties of the corresponding gradient networks (Z. Toroczkai, K. E. Bassler, Nature {\bf 428}, 716 (2004)). Using the Family model (F. Family, J. Phys. A, {\bf 19}, L441 (1986)) from surface-growth physics as single-step load-balancing dynamics, we show that the congestion pressure considerably drops on scale-free networks when compared with the same dynamics on random graphs. This is due to a structural transition of the corresponding gradient network clusters, which self-organize such as to reduce the congestion pressure. This reduction is enhanced when lowering the value of the connectivity exponent $λ$ towards 2.
dc.description10 pages, 6 figures
dc.identifierhttps://arxiv.org/abs/0803.3755
dc.identifierhttp://arxiv.org/abs/0803.3755
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/157499
dc.subjectStatistical Mechanics
dc.titleUsing relaxational dynamics to reduce network congestion
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