Efficient Monte Carlo evaluation of SDN resiliency

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Software defined networking (SDN) is an emerging technology for controlling flows through networks. Used in the context of industrial control systems, an objective is to design configurations that have built-in protection for hardware failures in the sense that the configuration has "baked-in" back-up routes. The objective is to leave the configuration static as long as possible, minimizing the need to have the controller push in new routing and filtering rules We have designed and implemented a tool that enables us to determine the complete connectivity map from an analysis of all switch configurations in the network. We can use this tool to explore the impact of a link failure, in particular to determine whether the failure induces loss of the ability to deliver a flow even after the built-in back-up routes are used. A measure of the original configuration's resilience to link failure is the mean number of link failures required to induce the first such loss of service. The computational cost of each link failure and subsequent analysis is large, so there is much to be gained by reducing the overall cost of obtaining a statistically valid estimate of resiliency. This paper shows that when analysis of a network state can identify all as-yet-unfailed links any one of whose failure would induce loss of a flow, then we can use the technique of importance sampling to estimate the mean number of links required to fail before some flow is lost, and analyze the potential for reducing the variance of the sample statistic. We provide both theoretical and empirical evidence for significant variance reduction.

Original languageEnglish (US)
Title of host publicationSIGSIM-PADS 2016 - Proceedings of the 2016 Annual ACM Conference on Principles of Advanced Discrete Simulation
PublisherAssociation for Computing Machinery, Inc
Pages143-152
Number of pages10
ISBN (Electronic)9781450337427
DOIs
StatePublished - May 15 2016
Event2016 Annual ACM Conference on Principles of Advanced Discrete Simulation, SIGSIM-PADS 2016 - Banff, Canada
Duration: May 15 2016May 18 2016

Publication series

NameSIGSIM-PADS 2016 - Proceedings of the 2016 Annual ACM Conference on Principles of Advanced Discrete Simulation

Other

Other2016 Annual ACM Conference on Principles of Advanced Discrete Simulation, SIGSIM-PADS 2016
CountryCanada
CityBanff
Period5/15/165/18/16

Keywords

  • Fast fail-over
  • Importance sampling
  • Monte Carlo
  • Reliability
  • Software defined networking

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Modeling and Simulation

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