Skip to main content

Analysis and Optimization of the Resilience Enhancement Circle via Data Farming

  • Conference paper
  • First Online:
Modelling and Simulation for Autonomous Systems (MESAS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11995))

  • 1451 Accesses

Abstract

The importance of communication networks increases with every new system and over the last 20 years these networks have become a critical infrastructure like the electricity network. Besides all cables and connections, the core of these networks are the information transfer systems with routers and switches. To guarantee the availability of these systems resilience is needed. The present paper evaluates possibilities to ensure resilience by the training for IT-Experts. For this purpose, typical errors and the way to fix these failures are inspected. A concept for combining the simulation of failures in systems and the mean time to restore (MTTR) was developed. Related to the information provided by the simulation, the concept was extended by details about the experts training level to specify the MTTR. Our approach is a possible way for providing information related to the field of training in context between experience and computer-generated information. Goal of our work is to enlarge the resilience of systems in critical infrastructures like communication networks by drawing conclusions about the IT-Experts training.

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

Notes

  1. 1.

    CCNA; Cisco Certified Network Associate.

References

  1. Laprie, J.-C.: From dependability to resilience. In: 38th IEEE/IFIP International Conference on Dependable Systems and Networks, pp. 8–9 (2008)

    Google Scholar 

  2. Amdal, J.R., Swigart, S.L.: Resilient Transportation Systems in a Post-Disaster Environment: A Case Study of Opportunities Realized and Missed in the Greater New Orleans Region (2010)

    Google Scholar 

  3. Southwick, S.M., Bonanno, G.A., Masten, A.S., Panter-Brick, C., Yehuda, R.: Resilience definitions, theory, and challenges: interdisciplinary perspectives. Eur. J. Psychotraumatol. 5(1), 1–14 (2014)

    Article  Google Scholar 

  4. Westrum, R.: A typology of resilience situations. In: Woods, D.D. (ed.) Resilience Engineering, pp. 67–78. CRC Press, Boca Raton (2017)

    Google Scholar 

  5. Woods, D.D.: Four concepts for resilience and the implications for the future of resilience engineering. Reliab. Eng. Syst. Saf. 141, 5–9 (2015)

    Article  Google Scholar 

  6. Schulte, W.: WAN - Wide Area Network: Einführung in die Technik und Protokolle. VDE VERLAG GmbH, Berlin (2014)

    Google Scholar 

  7. Barker, K., Ramirez-Marquez, J.E., Rocco, C.M.: Resilience-based network component importance measures. Reliab. Eng. Syst. Saf. 117, 89–97 (2013)

    Article  Google Scholar 

  8. Paxson, V., Floyd, S.: Wide area traffic: the failure of Poisson modeling. IEEE/ACM Trans. Netw. 3(3), 226–244 (1995)

    Article  Google Scholar 

  9. Faramondi, L., et al.: Network structural vulnerability: a multiobjective attacker perspective. IEEE Trans. Syst. Man Cybern. Syst. 49, 2036–2049 (2018)

    Article  MathSciNet  Google Scholar 

  10. Gill, P., Jain, N., Nagappan, N.: Understanding network failures in data centers: measurement, analysis, and implications. ACM SIGCOMM Comput. Commun. Rev. 41(4), 350–361 (2011)

    Article  Google Scholar 

  11. Crucitti, P., Latora, V., Marchiori, M.: Model for cascading failures in complex networks. Phys. Rev. E 69(4), 045104 (2004)

    Article  Google Scholar 

  12. Law, A.M., Kelton, W.D.: Simulation Modeling and Analysis, 3rd edn. McGraw-Hill, New York (2000)

    MATH  Google Scholar 

  13. Novaco, R.W., Cook, T.M., Sarason, I.G.: Military recruit training. In: Meichenbaum, D., Jaremko, M.E. (eds.) Stress Reduction and Prevention, pp. 377–418. Springer, Boston (1989). https://doi.org/10.1007/978-1-4899-0408-9_12

    Chapter  Google Scholar 

  14. Metzig, W., Schuster, M.: Lernen zu lernen, 9th edn. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-48897-3

    Book  Google Scholar 

  15. Dhamdhere, A., Teixeira, R., Dovrolis, C., Diot, C.: NetDiagnoser: troubleshooting network unreachabilities using end-to-end probes and routing data. In: Co-NEXT 2010 Proceedings of the 6th International Conference, pp. 18–30. ACM, New York (2010)

    Google Scholar 

  16. Wang, H.J., et al.: Automatic misconfiguration troubleshooting with peer pressure. In: OSDI 2004: 6th Symposium on Operating Systems Design and Implementation, pp. 245–257. USENIX Association, San Francisco (2004)

    Google Scholar 

  17. Kallfass, D., Schlaak, T.: NATO MSG-088 case study results to demonstrate the benefit of using data farming for military decision support. In: Proceedings of the Winter Simulation Conference, pp. 221–233. WSC, Berlin (2012)

    Google Scholar 

  18. Bein, W., Pickl, S., Tao, F.: Data analytics and optimization for decision support. Bus. Inf. Syst. Eng. 61(3), 255–256 (2019)

    Article  Google Scholar 

  19. Madni, A., Jackson, S.: Towards a conceptual framework for resilience engineering. IEEE Syst. J. 3, 181–191 (2009)

    Article  Google Scholar 

  20. Karwowski, W.: Ergonomics and human factors: the paradigms for science, engineering, design, technology and management of human-compatible systems. Ergonomics 48(5), 436–463 (2005)

    Article  Google Scholar 

  21. Bordetsky, A., Netzer, D.: TNT testbed for self-organizing tactical networking and collaboration. Naval Postgraduate School, Monterey, CA (2009)

    Google Scholar 

  22. Panteli, M., Mancarella, P.: The grid: stronger, bigger, smarter?: presenting a conceptual framework of power system resilience. IEEE Power Energy Mag. 13, 58–66 (2015)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Mario Dally or Sebastian Jahnen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dally, M., Jahnen, S., Moll, M., Pickl, S. (2020). Analysis and Optimization of the Resilience Enhancement Circle via Data Farming. In: Mazal, J., Fagiolini, A., Vasik, P. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2019. Lecture Notes in Computer Science(), vol 11995. Springer, Cham. https://doi.org/10.1007/978-3-030-43890-6_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-43890-6_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43889-0

  • Online ISBN: 978-3-030-43890-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics