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Heavy Hitter Detection on Multi-Pipeline Switches
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0002-5455-8910
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0002-9675-9729
2021 (English)In: Proceedings ANCS 2021 - Proceedings of the 2021 Symposium on Architectures for Networking and Communications Systems, Association for Computing Machinery (ACM) , 2021, p. 121-124Conference paper, Published paper (Refereed)
Abstract [en]

Recently, several applications have been designed and implemented to run entirely in the dataplane. However, most if not all the applications assume that network traffic traverses the same pipe, from ingress to egress inside the switch. While this seems to be a natural assumption, it does not hold for current programmable hardware that supports two to four pipes and network traffic is spread among the different pipes. As a consequence, several applications may not work properly in a multi-pipe architecture and need to be redesigned to fit into such architectural constraint. In this paper, we call the attention to this challenge and elaborate on an initial solution for counting heavy hitters (HH) in a multi-pipe hardware (MPHH). Our solution keeps the HH counter only in the egress pipeline while temporarily caching the hashes at the ingress pipeline. We then carry the hashes from ingress to egress by using data packets so that the HH are counted only in the egress pipeline. We present our design around this issue, the challenges observed so far and some initial results.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2021. p. 121-124
Keywords [en]
Heavy hitter detection, Multi-pipelines, Network monitoring, Programmable networks, Network architecture, 'current, Architectural constraints, Data-plane, Heavy hitte detection, Heavy-hitter, Multi-pipeline, Network traffic, Programmable hardware, Programmable network, Pipelines
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:kth:diva-316092DOI: 10.1145/3493425.3502760ISI: 000927857100016Scopus ID: 2-s2.0-85124129542OAI: oai:DiVA.org:kth-316092DiVA, id: diva2:1690517
Conference
16th ACM/IEEE Symposium on Architectures for Networking and Communications Systems, ANCS 2021, 13-16 December 2021
Note

Part of proceedings ISBN 9781450391689

QC 20220826

Available from: 2022-08-26 Created: 2022-08-26 Last updated: 2023-09-21Bibliographically approved

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Verdi, FabioChiesa, Marco

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Total: 34 hits
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