Skip to main content

Self-Healing Protocols for Infrastructural Networks

  • Conference paper
  • First Online:
Critical Information Infrastructures Security (CRITIS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8985))

  • 1519 Accesses

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999). http://dx.org/10.1126/science.286.5439.509

    Article  MathSciNet  MATH  Google Scholar 

  2. Barthelemy, M.: Spatial networks. Phy. Rep. 499(1–3), 1–101 (2011)

    Article  MathSciNet  Google Scholar 

  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). http://dx.org/10.1038/nature08932

    Article  Google Scholar 

  4. Csardi, G., Nepusz, T.: The igraph software package for complex network research. Inter. J. Complex Syst. 1695 (2006). http://igraph.sf.net

  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). http://dx.org/10.1209/0295-5075/97/68006

    Article  Google Scholar 

  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)

    Article  Google Scholar 

  7. Quattrociocchi, W., Caldarelli, G., Scala, A.: Self-healing networks: Redundancy and structure. PLoS ONE 9(2), e87986 (2014). http://dx.doi.org/10.1371%2Fjournal.pone.0087986

    Google Scholar 

  8. Santoro, N.: Design and Analysis of Distributed Algorithms. Wiley Series on Parallel and Distributed Computing. Wiley-Interscience, Hoboken (2006)

    Book  MATH  Google Scholar 

  9. Sudhakar, T.D., Srinivas, K.N.: Restoration of power network–a bibliographic survey. Eur. Trans. Electr. Power 21(1), 635–655 (2011). http://dx.org/10.1002/etep.467

    Article  Google Scholar 

  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)

    Article  Google Scholar 

  11. Watts, D.J., Strogatz, S.H.: Collective dynamics of /‘small-world/’ networks. Nature 393(6684), 440–442 (1998). http://dx.org/10.1038/30918

    Article  Google Scholar 

  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 

Download references

Acknowledgements

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Antonio Scala .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Scala, A., Quattrociocchi, W., Pagani, G.A., Aiello, M. (2016). Self-Healing Protocols for Infrastructural Networks. In: Panayiotou, C., Ellinas, G., Kyriakides, E., Polycarpou, M. (eds) Critical Information Infrastructures Security. CRITIS 2014. Lecture Notes in Computer Science(), vol 8985. Springer, Cham. https://doi.org/10.1007/978-3-319-31664-2_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-31664-2_31

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31663-5

  • Online ISBN: 978-3-319-31664-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics