Smolka, S;
Kumar, P;
Foster, N;
Kozen, D;
Silva, A;
(2017)
Cantor Meets Scott: Semantic Foundations for Probabilistic Networks.
In: Castagna, Giuseppe and Gordon, Andrew D., (eds.)
Proceedings of the 44th ACM SIGPLAN Symposium on Principles of Programming Languages - POPL 2017.
(pp. pp. 557-571).
ACM: Paris, France.
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Abstract
ProbNetKAT is a probabilistic extension of NetKAT with a denotational semantics based on Markov kernels. The language is expressive enough to generate continuous distributions, which raises the question of how to compute effectively in the language. This paper gives an new characterization of ProbNetKAT’s semantics using domain theory, which provides the foundation needed to build a practical implementation. We show how to use the semantics to approximate the behavior of arbitrary ProbNetKAT programs using distributions with finite support. We develop a prototype implementation and show how to use it to solve a variety of problems including characterizing the expected congestion induced by different routing schemes and reasoning probabilistically about reachability in a network.
| Type: | Proceedings paper |
|---|---|
| Title: | Cantor Meets Scott: Semantic Foundations for Probabilistic Networks |
| Event: | 44th ACM SIGPLAN Symposium on Principles of Programming Languages - POPL 2017 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3009837.3009843 |
| Publisher version: | https://doi.org/10.1145/3009837.3009843 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Software-defined networking, Probabilistic semantics, Kleene algebra with tests, Domain theory, NetKAT |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1523338 |
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