Skip to main content

Advertisement

SpringerLink
Log in

Provisioning dynamic and critical demand structures for geographically correlated failures

Using multi-disaster approach

  • Published:
Annals of Telecommunications Aims and scope Submit manuscript

Abstract

During disasters and other geographically correlated failures, the local telecommunications infrastructure undergoes a unique set of challenges. First, the telecommunications infrastructure is typically damaged reducing the capability to sustain the normal level of demands on the networks. Second, the demands on the telecommunications infrastructure increase typically by an order of magnitude. This is both for critical demands and non-critical demands. Third, critical demands, which may now be used to support disaster first responder and recovery efforts take on a crucial role. In this work, we propose multi-situational linear programming techniques to create disaster modes that take advantage of the non-coincidence of disasters in different geographic areas simultaneously reducing cost and improving restoration of demands during disasters. We also propose efficient heuristics to provision for disasters at a lower cost than standard provisioning with 1 + 1 redundancy. Additionally, we use diverse routing techniques to reduce the likelihood of damage to critical services. The restoration of demands during disasters also presents challenges for network provisioners. We present both heuristic and linear programming methods to assist with restoration of services in stressed network environments giving critical demands priority. Finally, service level agreements (SLAs) are used to provide a framework for these concepts.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Andrieux A, Czajkowski K, Dan A, Keahey K, Ludwig H, Nakata T, Pruyne J, Rofrano J, Tuecke S, Xu M (2007) Web services agreement specification (WS-agreement). In: Open Grid Forum, vol 128

  2. Badidi E (2011) A framework for brokered service level agreements in SOA environments. In: 2011 7th International Conference on Next Generation Web Services Practices (NWeSP). IEEE, pp 37–42

  3. Bardhan S, Milojicic D (2012) A mechanism to measure quality-of-service in a federated cloud environment. In: Proceedings of the 2012 Workshop on Cloud Services, Federation, and the 8th Open Cirrus Summit. ACM, pp 19–24

  4. Berbner R, Spahn M, Repp N, Heckmann O, Steinmetz R (2006) Heuristics for QoS-aware web service composition. In: 2006. ICWS’06. International Conference on Web Services. IEEE, pp 72–82

  5. Berkelaar M, Eikland K, Notebaert P lp_solve 5.5. 0.10. http://lpsolve.sourceforge.net/5.5 (2007). [Online; accessed 6-April-2016]

  6. Bianco P, Lewis GA, Merson P Service level agreements in service-oriented architecture environments. Technical report, Defense Technical Information Center (DTIC) (2008). http://www.dtic.mil/get-tr-doc/pdf? AD=ADA528751. [Online: http://www.dtic.mil/get-tr-doc/pdf? AD=ADA528751]

  7. Canfora G, Di Penta M, Esposito R, Villani ML (2005) An approach for QoS-aware service composition based on genetic algorithms. In: Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation. ACM, pp 1069– 1075

  8. Cetinkaya E, Alenazi M, Cheng Y, Peck A, Sterbenz J (2013) On the fitness of geographic graph generators for modelling physical level topologies. In: 2013 5th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). https://doi.org/10.1109/ICUMT.2013.6798402, pp 38–45

  9. Chekuri C, Khanna S, Shepherd FB (2004) The all-or-nothing multicommodity flow problem. In: Proceedings of the Thirty-sixth Annual ACM Symposium on Theory of Computing. ACM, pp 156–165

  10. Cheng Y, Gardner MT, Li J, May R, Medhi D, Sterbenz J (2015) Analysing geopath diversity and improving routing performance in optical networks. Comput Netw 82:50–67

    Article  Google Scholar 

  11. ITU-T Focus Group on Disaster Relief Systems, N.R., Recovery: Technical report on telecommunications and disaster mitigation. International Telecommunications Union (2013). http://www.itu.int/pub/T-FG-DRNRR. [Online; accessed 1-October-2016]

  12. Gabriel KR, Sokal RR (1969) A new statistical approach to geographic variation analysis. Syst Biol 18 (3):259–278

    Google Scholar 

  13. Gardner MT, Cheng Y, May R, Beard C, Sterbenz J, Medhi D (2016) Creating network resilience against disasters using service level agreements. In: 2016 12th International Conference on the Design of Reliable Communication Networks (DRCN’2016). IEEE, Paris

  14. Gerstel O, Sasaki GH (2001) Quality of protection (QoP): a quantitative unifying paradigm to protection service grades. In: OptiComm 2001: Optical Networking and Communications Conference. International Society for Optics and Photonics, pp 12–23

  15. Kuperman G, Modiano E, Narula-Tam A (2014) Analysis and algorithms for partial protection in mesh networks. J Opt Commun Netw 6(8):730–742

    Article  Google Scholar 

  16. ResiliNets KU (2012) Group: Resilinets topology - map viewer. http://www.ittc.ku.edu/resilinets/maps/. [Online; accessed 30-October-2013]

  17. Medhi D (1991) Diverse routing for survivability in a fiber-based sparse network. In: Proceedings of the IEEE International Conference on Communications (ICC’1991), Denver, pp 672–676

  18. Medhi D (1994) A unified approach to network survivability for teletraffic networks: Models, algorithms and analysis. IEEE Trans Commun 42(234):534–548

    Article  Google Scholar 

  19. Medhi D, Khurana R (1995) Optimization and performance of restoration schemes for wide-area teletraffic networks. J Netw Syst Manag 3(3):265–294

    Article  Google Scholar 

  20. Orlowski S, Wessäly R, Pióro M, Tomaszewski A (2010) SNDlib 1.0-survivable network design library. Networks 55(3):276–286

    Google Scholar 

  21. Pióro M, Medhi D (2004) Routing, flow, and capacity design in communication and computer networks. Elsevier, Amsterdam

    MATH  Google Scholar 

  22. Rahman MR, Boutaba R (2013) Svne: Survivable virtual network embedding algorithms for network virtualization. IEEE Trans Netw Serv Manag 10(2):105–118

    Article  Google Scholar 

  23. Srivastava S, Thirumalasetty SR, Medhi D (2005) Network traffic engineering with varied levels of protection in the next generation Internet. In: Performance Evaluation and Planning Methods for the Next Generation Internet. Springer, pp 99–124

  24. Sterbenz J, Cetinkaya EK, Hameed MA, Jabbar A, Qian S, Rohrer JP (2011) Evaluation of network resilience, survivability, and disruption tolerance: analysis, topology generation, simulation, and experimentation. Telecommun Syst 52:1–32

    Google Scholar 

  25. Sterbenz J, Hutchison D, Çetinkaya EK, Jabbar A, Rohrer JP, Schöller M, Smith P (2010) Resilience and survivability in communication networks: Strategies, principles, and survey of disciplines. Comput Netw 54(8):1245–1265. https://doi.org/10.1016/j.comnet.2010.03.005. http://linkinghub.elsevier.com/retrieve/pii/S1389128610000824

    Article  MATH  Google Scholar 

Download references

Funding

This work is partially supported by NSF grants CNS-1219028 and CNS-1217736.

Author information

Authors and Affiliations

  1. Department of Computer Science and Electrical Engineering, University of Missouri, Kansas City, 5110 Rockhill Road, Kansas City, MO, 64110, USA

    M. Todd Gardner, Cory Beard & Deep Medhi

  2. Amazon Technologies, Seattle, WA, USA

    Yufei Cheng

  3. Department of Electrical Engineering & Computer Science and Information & Telecommunication Technology Center, The University of Kansas, Lawrence, KS, 66045, USA

    James P. G. Sterbenz

  4. School of Computing and Communications, Lancaster University, Lancaster, LA1 4WA, UK

    James P. G. Sterbenz

Authors
  1. M. Todd Gardner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yufei Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cory Beard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. James P. G. Sterbenz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Deep Medhi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Todd Gardner.

Additional information

Yufei Cheng completed this work while at the University of Kansas.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gardner, M.T., Cheng, Y., Beard, C. et al. Provisioning dynamic and critical demand structures for geographically correlated failures. Ann. Telecommun. 73, 111–125 (2018). https://doi.org/10.1007/s12243-017-0618-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12243-017-0618-z

Keywords

Search

Navigation