Robustness of Random Scale-Free Networks against Cascading Failure under Edge Attacks

To control the spread of cascading failure on scale-free networks, we propose a new model with the betweenness centrality and the degrees of the nodes which are combined. The effects of the parameters of the edge weight on cascading dynamics are investigated. Five metrics to evaluate the robustness of the network are given: the threshold parameter ([Formula: see text]), the proportion of collapsed edges ([Formula: see text]), the proportion of collapsed nodes ([Formula: see text]), the number of nodes in the largest connected component ([Formula: see text]) and the number of the connected component ([Formula: see text]). Compared with the degrees of nodes’ model and the betweenness of the nodes’ model, the new model could control the spread of cascading failure more significantly. This work might be helpful for preventing and mitigating cascading failure in real life, especially for small load networks.

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The Prisoner’s Dilemma Game on Random Scale-Free Networks

Evolutionary Games in Complex Topologies - Springer Theses ◽

10.1007/978-3-642-30117-9_5 ◽

2012 ◽

pp. 87-100

Author(s):

Julia Poncela Casasnovas

Keyword(s):

Prisoner's Dilemma ◽

Prisoner’S Dilemma ◽

Prisoner’S Dilemma Game ◽

Scale Free ◽

Scale Free Networks ◽

Prisoner's Dilemma Game ◽

Random Scale

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Uncertainty of cooperation in random scale-free networks

Physica A Statistical Mechanics and its Applications ◽

10.1016/j.physa.2009.03.018 ◽

2009 ◽

Vol 388 (13) ◽

pp. 2757-2761 ◽

Cited By ~ 4

Author(s):

Eleni Arapaki

Keyword(s):

Scale Free ◽

Scale Free Networks ◽

Random Scale

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Dynamics of load entropy during cascading failure propagation in scale-free networks

Physics Letters A ◽

10.1016/j.physleta.2008.07.034 ◽

2008 ◽

Vol 372 (36) ◽

pp. 5778-5782 ◽

Cited By ~ 40

Author(s):

Z.J. Bao ◽

Y.J. Cao ◽

L.J. Ding ◽

Z.X. Han ◽

G.Z. Wang

Keyword(s):

Cascading Failure ◽

Scale Free ◽

Scale Free Networks ◽

Failure Propagation

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Asymptotic Behavior and Synchronizability Characteristics of a Class of Recurrent Neural Networks

Neural Computation ◽

10.1162/neco.2007.19.9.2492 ◽

2007 ◽

Vol 19 (9) ◽

pp. 2492-2514 ◽

Cited By ~ 2

Author(s):

Christof Cebulla

Keyword(s):

Neural Network ◽

Asymptotic Behavior ◽

Recurrent Neural Networks ◽

Random Networks ◽

Scale Free ◽

Scale Free Networks ◽

Zhang Model ◽

Random Scale ◽

Connectivity Distribution ◽

Time Asymptotic Behavior

We propose an approach to the analysis of the influence of the topology of a neural network on its synchronizability in the sense of equal output activity rates given by a particular neural network model. The model we introduce is a variation of the Zhang model. We investigate the time-asymptotic behavior of the corresponding dynamical system (in particular, the conditions for the existence of an invariant compact asymptotic set) and apply the results of the synchronizability analysis on a class of random scale free networks and to the classical random networks with Poisson connectivity distribution.

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