Self-Healing Protocols for Infrastructural Networks

  • Antonio ScalaEmail author
  • Walter Quattrociocchi
  • Giuliano Andrea Pagani
  • Marco Aiello
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8985)


A crucial feature in implementing the next generation of smart grids is how to introduce self-healing capabilities allowing to ensure a high quality of service to the users. We show how distributed communication protocols can enrich complex networks with self-healing capabilities; an obvious field of applications are infrastructural networks. In particular, we consider the case where the presence of redundant links allows to recover the connectivity of the system. We then analyse the interplay between redundancies and topology in improving the resilience of networked infrastructures to multiple failures; in particular, we measure the fraction of nodes still served for increasing levels of network damages. Hence, we consider healing performances respect to different network topologies (planar, small-world, scale-free) corresponding to various degree of realism. We find that the most balanced strategy to enhances networks’ resilience to multiple failures while avoiding large economic expenses is to introduce a finite fraction of long-range connections.


Critical infrastructures Distributed protocols Complex networks Self-healing 



AS and WQ thank US grant HDTRA1-11-1-0048, CNR-PNR National Project Crisis-Lab and EU FET project MULTIPLEX nr.317532. AS thanks EU HOME/2013/CIPS/AG/4000005013 project CI2C. The contents of the paper do not necessarily reflect the position or the policy of funding parties. AS thanks Claudio Mazzariello for very useful discussions on routing algorithms and Michele Festuccia for pointing out the technological feasibility of our approach.


  1. 1.
    Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999). MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Barthelemy, M.: Spatial networks. Phy. Rep. 499(1–3), 1–101 (2011)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Buldyrev, S.V., Parshani, R., Paul, G., Stanley, H.E., Havlin, S.: Catastrophic cascade of failures in interdependent networks. Nature 464(7291), 1025–1028 (2010). CrossRefGoogle Scholar
  4. 4.
    Csardi, G., Nepusz, T.: The igraph software package for complex network research. Inter. J. Complex Syst. 1695 (2006).
  5. 5.
    D’Agostino, G., Scala, A., Zlatić, V., Caldarelli, G.: Robustness and assortativity for diffusion-like processes in scale-free networks. EpPL 97(6), 68006 (2012). CrossRefGoogle Scholar
  6. 6.
    Pagani, G.A., Aiello, M.: Towards decentralization: a topological investigation of the medium and low voltage grids. IEEE Trans. Smart Grid 2(3), 538–547 (2011)CrossRefGoogle Scholar
  7. 7.
    Quattrociocchi, W., Caldarelli, G., Scala, A.: Self-healing networks: Redundancy and structure. PLoS ONE 9(2), e87986 (2014). Google Scholar
  8. 8.
    Santoro, N.: Design and Analysis of Distributed Algorithms. Wiley Series on Parallel and Distributed Computing. Wiley-Interscience, Hoboken (2006)CrossRefzbMATHGoogle Scholar
  9. 9.
    Sudhakar, T.D., Srinivas, K.N.: Restoration of power network–a bibliographic survey. Eur. Trans. Electr. Power 21(1), 635–655 (2011). CrossRefGoogle Scholar
  10. 10.
    Wang, Z., Scaglione, A., Thomas, R.: Generating statistically correct random topologies for testing smart grid communication and control networks. IEEE Trans. Smart Grid 1(1), 28–39 (2010)CrossRefGoogle Scholar
  11. 11.
    Watts, D.J., Strogatz, S.H.: Collective dynamics of /‘small-world/’ networks. Nature 393(6684), 440–442 (1998). CrossRefGoogle Scholar
  12. 12.
    Wilson, D.B.: Generating random spanning trees more quickly than the cover time. In: Proceedings of the 28th annuan ACM Symposium on the Theory of Computing, pp. 296–303. ACM (1996)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Antonio Scala
    • 1
    • 2
    • 3
    Email author
  • Walter Quattrociocchi
    • 2
    • 3
  • Giuliano Andrea Pagani
    • 4
  • Marco Aiello
    • 4
  1. 1.ISC-CNR Physics DepartmentUniversity “La Sapienza”RomaItaly
  2. 2.IMT Alti Studi LuccaLuccaItaly
  3. 3.London Institute of Mathematical SciencesLondonUK
  4. 4.Distributed Systems Group, Johann Bernoulli Institute for Mathematics and Computer ScienceUniversity of GroningenGroningenThe Netherlands

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