Actor-based model checking for Software-Defined Networks

Software-Defined Networking (SDN) is a networking paradigm that has become increasingly popular in the last decade. The unprecedented control over the global behaviour of the network it provides opens a range of new opportunities for formal methods and much work has appeared in the last few years on...

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Bibliographic Details
Published inJournal of logical and algebraic methods in programming Vol. 118; p. 100617
Main Authors Albert, Elvira, Gómez-Zamalloa, Miguel, Isabel, Miguel, Rubio, Albert, Sammartino, Matteo, Silva, Alexandra
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.01.2021
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Summary:Software-Defined Networking (SDN) is a networking paradigm that has become increasingly popular in the last decade. The unprecedented control over the global behaviour of the network it provides opens a range of new opportunities for formal methods and much work has appeared in the last few years on providing bridges between SDN and verification. This article advances this research line and provides a link between SDN and traditional work on formal methods for verification of concurrent and distributed software—actor-based modelling. We show how SDN programs can be seamlessly modelled using actors, and thus existing advanced model checking techniques developed for actors can be directly applied to verify a range of properties of SDNs, including consistency of flow tables, violation of safety policies, and forwarding loops. Our model checker for SDNs is available through an online web interface, that also provides the SDN actor-models for a number of well-known SDN benchmarks. •This work includes a formalization of the semantics of Software-Defined Networks.•We present SDN-Actors: an encoding of all basic components of an SDN network.•We provide an implementation of one of the OpenFlow barrier messages.•A model checker for our SDN models is built on top of the SYCO tool.•We show several case studies of SDN to illustrate the potential of the approach.
ISSN:2352-2208
DOI:10.1016/j.jlamp.2020.100617