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Self-healing networks: redundancy and structure.

Walter Quattrociocchi1, Guido Caldarelli2, Antonio Scala3

  • 1Laboratory for the modeling of biological and socio-technical systems, Northeastern University, Boston, Massachusetts, United States of America ; LIMS the London Institute of Mathematical Sciences, Mayfair, London, United Kingdom ; IMT Alti Studi Lucca, Lucca, Italy.

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This study introduces self-healing complex networks using redundant links for resilience. Small-world networks with long-range connections show enhanced recovery from failures, comparable to scale-free networks.

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Area of Science:

  • Complex networks modeling
  • Network resilience
  • Distributed systems

Background:

  • Complex networks are susceptible to failures.
  • Infrastructure networks require high resilience.
  • Self-healing mechanisms are crucial for system robustness.

Purpose of the Study:

  • To introduce self-healing capabilities in complex network modeling.
  • To analyze the impact of redundancy on network resilience to failures.
  • To investigate healing performance across different network topologies.

Main Methods:

  • Implementing distributed communication protocols for self-healing.
  • Exploiting redundant links to recover system connectivity.
  • Measuring the fraction of served nodes under increasing network damage levels.

Main Results:

  • Redundancy significantly enhances resilience to multiple failures.
  • Small-world networks with long-range connections exhibit superior healing performance.
  • Performance of small-world networks is comparable to scale-free networks.

Conclusions:

  • Self-healing mechanisms, particularly in small-world networks, improve resilience.
  • Redundant links are key to effective self-healing in complex systems.
  • Applications include critical infrastructural networks like power and water distribution.