1,543 research outputs found
Cascading failures in spatially-embedded random networks
Cascading failures constitute an important vulnerability of interconnected
systems. Here we focus on the study of such failures on networks in which the
connectivity of nodes is constrained by geographical distance. Specifically, we
use random geometric graphs as representative examples of such spatial
networks, and study the properties of cascading failures on them in the
presence of distributed flow. The key finding of this study is that the process
of cascading failures is non-self-averaging on spatial networks, and thus,
aggregate inferences made from analyzing an ensemble of such networks lead to
incorrect conclusions when applied to a single network, no matter how large the
network is. We demonstrate that this lack of self-averaging disappears with the
introduction of a small fraction of long-range links into the network. We
simulate the well studied preemptive node removal strategy for cascade
mitigation and show that it is largely ineffective in the case of spatial
networks. We introduce an altruistic strategy designed to limit the loss of
network nodes in the event of a cascade triggering failure and show that it
performs better than the preemptive strategy. Finally, we consider a real-world
spatial network viz. a European power transmission network and validate that
our findings from the study of random geometric graphs are also borne out by
simulations of cascading failures on the empirical network.Comment: 13 pages, 15 figure
Cascading Failures in Complex Networks
Cascading failure is a potentially devastating process that spreads on
real-world complex networks and can impact the integrity of wide-ranging
infrastructures, natural systems, and societal cohesiveness. One of the
essential features that create complex network vulnerability to failure
propagation is the dependency among their components, exposing entire systems
to significant risks from destabilizing hazards such as human attacks, natural
disasters or internal breakdowns. Developing realistic models for cascading
failures as well as strategies to halt and mitigate the failure propagation can
point to new approaches to restoring and strengthening real-world networks. In
this review, we summarize recent progress on models developed based on physics
and complex network science to understand the mechanisms, dynamics and overall
impact of cascading failures. We present models for cascading failures in
single networks and interdependent networks and explain how different dynamic
propagation mechanisms can lead to an abrupt collapse and a rich dynamic
behavior. Finally, we close the review with novel emerging strategies for
containing cascades of failures and discuss open questions that remain to be
addressed.Comment: This review has been accepted for publication in the Journal of
Complex Networks Published by Oxford University Pres
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