Avalanche dynamics driven by adaptive rewirings in complex networks

Abstract

We introduce a toy model displaying the avalanche dynamics of failure in scale-free networks. In the model, the network growth is based on the Barabási and Albert model and each node is assigned a capacity or tolerance, which is constant irrespective of node index. The degree of each node increases over time. When the degree of a node exceeds its capacity, it fails and each link connected to it is is rewired to other unconnected nodes by following the preferential attachment rule. Such a rewiring edge may trigger another failure. This dynamic process can occur successively, and it exhibits a self-organized critical behavior in which the avalanche size distribution follows a power law. The associated exponent is $τ\approx 2.6(1)$. The entire system breaks down when any rewired edges cannot locate target nodes: the time at which this occurs is referred to as the breaking time. We obtain the breaking time as a function of the capacity. Moreover, using extreme value statistics, we determine the distribution function of the breaking time.