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Provisioning dynamic and critical demand structures for geographically correlated failures

Using multi-disaster approach

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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.

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Funding

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

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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
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  2. Yufei Cheng
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  3. Cory Beard
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  4. James P. G. Sterbenz
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  5. Deep Medhi
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Corresponding author

Correspondence to M. Todd Gardner.

Additional information

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

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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

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

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