Non-Markovian recovery makes complex networks more resilient against large-scale failures

@article{Lin2020NonMarkovianRM,
  title={Non-Markovian recovery makes complex networks more resilient against large-scale failures},
  author={Zhaohua Lin and Mi Feng and Ming Tang and Zonghua Liu and Chao Xu and Pak Ming Hui and Ying-Cheng Lai},
  journal={Nature Communications},
  year={2020},
  volume={11}
}
  • Zhaohua Lin, Mi Feng, +4 authors Ying-Cheng Lai
  • Published 2020
  • Biology, Mathematics, Medicine, Physics
  • Nature Communications
  • Non-Markovian spontaneous recovery processes with a time delay (memory) are ubiquitous in the real world. How does the non-Markovian characteristic affect failure propagation in complex networks? We consider failures due to internal causes at the nodal level and external failures due to an adverse environment, and develop a pair approximation analysis taking into account the two-node correlation. In general, a high failure stationary state can arise, corresponding to large-scale failures that… CONTINUE READING

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