Network protection with guaranteed recovery times using recovery domains
Name
Modiano_Network protection with guaranteed.pdf
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654.93 KB
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Adobe PDF
Checksum (MD5)
ef04d2e959a1b52314b2812a055b5541
Author(s)
Kuperman, Gregory
Modiano, Eytan H.
Date Issued
April 2013
Journal
2013 Proceedings IEEE INFOCOM
Publisher
Institute of Electrical and Electronics Engineers
Citation
Kuperman, Greg, and Eytan Modiano. “Network protection with guaranteed recovery times using recovery domains.” In 2013 Proceedings IEEE INFOCOM, 14-19 April 2013, Turin, Italy. pp.692-700. Institute of Electrical and Electronics Engineers, 2013.
Version
Author's final manuscript
Abstract
We consider the problem of providing network protection that guarantees the maximum amount of time that flow can be interrupted after a failure. This is in contrast to schemes that offer no recovery time guarantees, such as IP rerouting, or the prevalent local recovery scheme of Fast ReRoute, which often over-provisions resources to meet recovery time constraints. To meet these recovery time guarantees, we provide a novel and flexible solution by partitioning the network into failure-independent “recovery domains”, where within each domain, the maximum amount of time to recover from a failure is guaranteed. We show the recovery domain problem to be NP-Hard, and develop an optimal solution in the form of an MILP for both the case when backup capacity can and cannot be shared. This provides protection with guaranteed recovery times using up to 45% less protection resources than local recovery. We demonstrate that the network-wide optimal recovery domain solution can be decomposed into a set of easier to solve subproblems. This allows for the development of flexible and efficient solutions, including an optimal algorithm using Lagrangian relaxation, which simulations show to converge rapidly to an optimal solution. Additionally, an algorithm is developed for when backup sharing is allowed. For dynamic arrivals, this algorithm performs better than the solution that tries to greedily optimize for each incoming demand.
MIT Department
Lincoln Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1109/INFCOM.2013.6566855
