Artículo
Failure-recovery model with competition between failures in complex networks: A dynamical approach
Fecha de publicación:
09/2016
Editorial:
IOP Publishing
Revista:
Journal of Statistical Mechanics: Theory and Experiment
ISSN:
1742-5468
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Real systems are usually composed by units or nodes whose activity can be interrupted and restored intermittently due to complex interactions not only with the environment, but also with the same system. Majdandžić et al (2014 Nat. Phys. 10 34) proposed a model to study systems in which active nodes fail and recover spontaneously in a complex network and found that in the steady state the density of active nodes can exhibit an abrupt transition and hysteresis depending on the values of the parameters. Here we investigate a model of recovery-failure from a dynamical point of view. Using an effective degree approach we find that the systems can exhibit a temporal sharp decrease in the fraction of active nodes. Moreover we show that, depending on the values of the parameters, the fraction of active nodes has an oscillatory regime which we explain as a competition between different failure processes. We also find that in the non-oscillatory regime, the critical fraction of active nodes presents a discontinuous drop which can be related to a 'targeted' k-core percolation process. Finally, using mean field equations we analyze the space of parameters at which hysteresis and oscillatory regimes can be found.
Palabras clave:
NETWORKS
,
NONLINEAR DYNAMICS
,
PERCOLATION PROBLEMS
,
RANDOM GRAPHS
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Articulos(IFEG)
Articulos de INST.DE FISICA ENRIQUE GAVIOLA
Articulos de INST.DE FISICA ENRIQUE GAVIOLA
Articulos(IFIMAR)
Articulos de INST.DE INVESTIGACIONES FISICAS DE MAR DEL PLATA
Articulos de INST.DE INVESTIGACIONES FISICAS DE MAR DEL PLATA
Citación
Valdez, Lucas Daniel; Di Muro, Matias Alberto; Braunstein, Lidia Adriana; Failure-recovery model with competition between failures in complex networks: A dynamical approach; IOP Publishing; Journal of Statistical Mechanics: Theory and Experiment; 2016; 9; 9-2016; 1-24
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