AalWiNes: A fast and quantitative what-if analysis tool for MPLS networks

Peter Gjøl Jensen, Dan Kristiansen, Stefan Schmid, Morten Konggaard Schou, Bernhard Clemens Schrenk, Jiri Srba

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Abstrakt

We present an automated what-if analysis tool AalWiNes for MPLS networks which allows us to verify both logical properties (e.g., related to the policy compliance) as well as quantitative properties (e.g., concerning the latency) under multiple link failures. Our tool relies on weighted pushdown automata, a quantitative extension of classic automata theory, and takes into account the actual dataplane configuration, rendering it especially useful for debugging. In particular, our tool collects the different router forwarding tables and then builds a pushdown system, on which quantitative reachability is performed based on an expressive query language. Our experiments show that our tool outperforms state-of-the-art approaches (which until now have been restricted to logical properties) by several orders of magnitude; furthermore, our quantitative extension only entails a moderate overhead in terms of runtime. The tool comes with a platform-independent user interface and is publicly available as open-source, together with all other experimental artefacts.

OriginalsprogEngelsk
TitelCoNEXT '20 : Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies
Antal sider8
ForlagAssociation for Computing Machinery
Publikationsdato23 nov. 2020
Sider474-481
ISBN (Trykt)9781450379489
DOI
StatusUdgivet - 23 nov. 2020
Begivenhed16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020 - Barcelona, Spanien
Varighed: 1 dec. 20204 dec. 2020

Konference

Konference16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020
LandSpanien
ByBarcelona
Periode01/12/202004/12/2020
SponsorACM SigComm

Bibliografisk note

Funding Information:
Acknowledgements. We thank Henrik T. Jensen from NORDUnet for providing us with configuration data. The research is supported by DFF project QASNET and WWTF project ICT19-045.

Publisher Copyright:
© 2020 ACM.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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