Memory-efficient membership encoding in switches

Mengying Pan, Robert MacDavid, Shir Landau-Feibish, Jennifer Rexford

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


Network applications often define policies to manage network traffic based on its attributes (e.g., a service chain, valid next-hops, permission flags). These policies match against packets' attributes in switches before being applied. However, the prior works of identifying attributes all incur a high memory cost in the data plane. This paper presents MEME, a scheme that clusters the attributes in packets to reduce the memory usage. MEME also leverages match-action tables and reconfigurable parsers on modern hardware switches to achieve 87.7% lower memory usage, and applies a graph algorithm to achieve 1-2 orders of magnitude faster compilation time than the prior state of the art [12]. These performance gains pave the way for deployment of a real system desired by the world's largest Internet Exchange Points.

Original languageEnglish (US)
Title of host publicationSOSR 2020 - Proceedings of the 2020 Symposium on SDN Research
PublisherAssociation for Computing Machinery, Inc
Number of pages7
ISBN (Electronic)9781450371018
StatePublished - Mar 3 2020
Event2020 Symposium on SDN Research, SOSR 2020 - San Jose, United States
Duration: Mar 3 2020 → …

Publication series

NameSOSR 2020 - Proceedings of the 2020 Symposium on SDN Research


Conference2020 Symposium on SDN Research, SOSR 2020
Country/TerritoryUnited States
CitySan Jose
Period3/3/20 → …

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software


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