Demo: Structural Network Minimization: A Case of Reflective Networking

Mubashir Anwar, Anduo Wang, Fangping Lan, Matthew Caesar

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


Traditional network state management focuses on packets that exercise network structures (configurations, procedures) and testify semantics (intentions), but provides little insights into how the structure actually "causes"the semantics. In response to this missed opportunity, we propose reflective networking, which features a network structure capable of altering itself with a causal connection to its semantics. Specifically, we investigate the network datalog structure and the chase, a process that transforms datalog programs by "executing"intents (semantic constraints) that are themselves expressed in datalog. To illustrate the usefulness of reflective networking, this demonstration presents a first use case: we developed an intuitive specification of routing in datalog, and employed the chase to summarize a network's routing behavior by minimizing (repeatedly transforming) the corresponding datalog program.

Original languageEnglish (US)
Title of host publicationSIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference
PublisherAssociation for Computing Machinery
Number of pages3
ISBN (Electronic)9798400702365
StatePublished - Sep 10 2023
EventACM SIGCOMM 2023 Conference - New York, United States
Duration: Sep 10 2023Sep 14 2023

Publication series

NameSIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference


ConferenceACM SIGCOMM 2023 Conference
Country/TerritoryUnited States
CityNew York


  • datalog minimization
  • network management
  • reflective programming
  • the chase

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Computer Networks and Communications


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