SwiSh: Distributed Shared State Abstractions for Programmable Switches

Lior Zeno, Dan R.K. Ports, Jacob Nelson, Daehyeok Kim, Shir Landau Feibish, Idit Keidar, Arik Rinberg, Alon Rashelbach, Igor De-Paula, Mark Silberstein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We design and evaluate SwiSh, a distributed shared state management layer for data-plane P4 programs. SwiSh enables running scalable stateful distributed network functions on programmable switches entirely in the data-plane. We explore several schemes to build a shared variable abstraction, which differ in consistency, performance, and in-switch implementation complexity. We introduce the novel Strong Delayed-Writes (SDW) protocol which offers consistent snapshots of shared data-plane objects with semantics known as r-relaxed strong linearizability, enabling implementation of distributed concurrent sketches with precise error bounds. We implement strong, eventual, and SDW consistency protocols in Tofino switches, and compare their performance in microbenchmarks and three realistic network functions, NAT, DDoS detector, and rate limiter. Our results show that the distributed state management in the data plane is practical, and outperforms centralized solutions by up to four orders of magnitude in update throughput and replication latency.

Original languageEnglish
Title of host publicationProceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2022
PublisherUSENIX Association
Pages171-191
Number of pages21
ISBN (Electronic)9781939133274
StatePublished - 2022
Event19th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2022 - Renton, United States
Duration: 4 Apr 20226 Apr 2022

Publication series

NameProceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2022

Conference

Conference19th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2022
Country/TerritoryUnited States
CityRenton
Period4/04/226/04/22

Bibliographical note

Funding Information:
We would like to thank the anonymous reviewers and our shepherd, Dejan Kostic, for their insightful comments and constructive feedback. Lior Zeno was partially supported by the HPI-Technion Research School. We gratefully acknowledge support from Israel Science Foundation (grants 980/21 and 1027/18) and Technion Hiroshi Fujiwara Cyber Security Research Center.

Publisher Copyright:
© 2022 by The USENIX Association. All Rights Reserved.

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