Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Heavy Hitter Detection on Multi-Pipeline Switches
KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.ORCID-id: 0000-0002-5455-8910
KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.ORCID-id: 0000-0002-9675-9729
2021 (engelsk)Inngår i: Proceedings ANCS 2021 - Proceedings of the 2021 Symposium on Architectures for Networking and Communications Systems, Association for Computing Machinery (ACM) , 2021, s. 121-124Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Association for Computing Machinery (ACM) , 2021. s. 121-124
Emneord [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
HSV kategori
Identifikatorer
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
Konferanse
16th ACM/IEEE Symposium on Architectures for Networking and Communications Systems, ANCS 2021, 13-16 December 2021
Merknad

Part of proceedings ISBN 9781450391689

QC 20220826

Tilgjengelig fra: 2022-08-26 Laget: 2022-08-26 Sist oppdatert: 2023-09-21bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Person

Verdi, FabioChiesa, Marco

Søk i DiVA

Av forfatter/redaktør
Verdi, FabioChiesa, Marco
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric

doi
urn-nbn
Totalt: 65 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf