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Impact of embedding on predictability of failure-recovery dynamics in networks
Failure, damage spread and recovery crucially underlie many spatially
embedded networked systems ranging from transportation structures to the human
body. Here we study the interplay between spontaneous damage, induced failure
and recovery in both embedded and non-embedded networks. In our model the
network's components follow three realistic processes that capture these
features: (i) spontaneous failure of a component independent of the
neighborhood (internal failure), (ii) failure induced by failed neighboring
nodes (external failure) and (iii) spontaneous recovery of a component.We
identify a metastable domain in the global network phase diagram spanned by the
model's control parameters where dramatic hysteresis effects and random
switching between two coexisting states are observed. The loss of
predictability due to these effects depend on the characteristic link length of
the embedded system. For the Euclidean lattice in particular, hysteresis and
switching only occur in an extremely narrow region of the parameter space
compared to random networks. We develop a unifying theory which links the
dynamics of our model to contact processes. Our unifying framework may help to
better understand predictability and controllability in spatially embedded and
random networks where spontaneous recovery of components can mitigate
spontaneous failure and damage spread in the global network.Comment: 22 pages, 20 figure
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