Failure and recovery in dynamical networks View Full Text


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Article Info

DATE

2017-02-03

AUTHORS

L. Böttcher, M. Luković, J. Nagler, S. Havlin, H. J. Herrmann

ABSTRACT

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. This dynamics depends 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 controllability in spatially embedded and random networks where spontaneous recovery of components can mitigate spontaneous failure and damage spread in dynamical networks. More... »

PAGES

41729

References to SciGraph publications

  • 2013-05-01. Globally networked risks and how to respond in NATURE
  • 2008-02-20. Ecology for bankers in NATURE
  • 2009-10-13. Systemic risk in a unifying framework for cascading processes on networks in THE EUROPEAN PHYSICAL JOURNAL B
  • 1982-12. On phase transitions in Schlögl's second model in ZEITSCHRIFT FÜR PHYSIK B CONDENSED MATTER
  • 2015-07-01. Anomalous critical and supercritical phenomena in explosive percolation in NATURE PHYSICS
  • 2013-08-25. The extreme vulnerability of interdependent spatially embedded networks in NATURE PHYSICS
  • 2016-01-29. Emergence of core–peripheries in networks in NATURE COMMUNICATIONS
  • 2013-07-26. Crackling noise in fractional percolation in NATURE COMMUNICATIONS
  • 1989-08. Oscillations in the perception of ambiguous patterns a model based on synergetics in BIOLOGICAL CYBERNETICS
  • 2013-12-01. Spontaneous recovery in dynamical networks in NATURE PHYSICS
  • 1979. Catastrophe Theory in STRUCTURAL STABILITY IN PHYSICS
  • 2000-07. Error and attack tolerance of complex networks in NATURE
  • 2015. Stochastic Dynamics and Irreversibility in NONE
  • 2016-02-22. Universality in boundary domain growth by sudden bridging in SCIENTIFIC REPORTS
  • 2015-11-16. Disease-induced resource constraints can trigger explosive epidemics in SCIENTIFIC REPORTS
  • 2008. Springer in ENCYCLOPEDIA OF GENETICS, GENOMICS, PROTEOMICS AND INFORMATICS
  • 2011-01-19. Systemic risk in banking ecosystems in NATURE
  • 2010-12-17. Network medicine: a network-based approach to human disease in NATURE REVIEWS GENETICS
  • 2012-01. Network physiology reveals relations between network topology and physiological function in NATURE COMMUNICATIONS
  • 2011-01-16. Impact of single links in competitive percolation in NATURE PHYSICS
  • 2010-04. Catastrophic cascade of failures in interdependent networks in NATURE
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/srep41729

    DOI

    http://dx.doi.org/10.1038/srep41729

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1083524763

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28155876


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