Cantor meets Scott: semantic foundations for probabilistic networks
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2017
- Source ID
- 10.1145/3093333.3009843
Entities
People
- Alexandra Silva
- Dexter Kozen
- Nate Foster
- Praveen Kumar
- Steffen Smolka
Organizations
- Cornell University
- Dutch Research Council
- National Science Foundation
- National Security Agency
- Office of Naval Research
- University College London