Feature Study on a Programmable Network Traffic Classifier

Keissy Guerra Perez; Xin Yang; Sandra Scott-Hayward; Sakir Sezer

doi:10.1109/SOCC.2016.7905446

Feature Study on a Programmable Network Traffic Classifier

Keissy Guerra Perez, Xin Yang, Sandra Scott-Hayward, Sakir Sezer

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

385 Downloads (Pure)

Abstract

Monitoring and tracking of IP traffic flows are essential for network services (i.e. packet forwarding). Packet header lookup is the main part of flow identification by determining the predefined matching action for each incoming flow. In this paper, an improved header lookup and flow rule update solution is investigated. A detailed study of several well-known lookup algorithms reveals that searching individual packet header field and combining the results achieve high lookup speed and flexibility. The proposed hybrid lookup architecture is comprised of various lookup algorithms, which are selected based on the user applications and system requirements.

Original language	English
Title of host publication	2016 29th IEEE International System-on-Chip Conference (SOCC): Proceedings
Pages	108-113
Number of pages	6
ISBN (Electronic)	978-1-5090-1367-8
DOIs	https://doi.org/10.1109/SOCC.2016.7905446
Publication status	Published - 24 Apr 2017
Event	29th IEEE International System-on-Chip Conference - Renaissance Seattle Hotel, Seattle, United States Duration: 06 Sept 2016 → 09 Sept 2016 http://www.ieee-socc.org/

Publication series

Name	International SOC Conference (SOCC). Proceedings
Publisher	IEEE
ISSN (Print)	2164-1676

Conference

Conference	29th IEEE International System-on-Chip Conference
Abbreviated title	IEEE SOCC 2016
Country/Territory	United States
City	Seattle
Period	06/09/2016 → 09/09/2016
Internet address	http://www.ieee-socc.org/

Keywords

packet classification; multi-dimensional lookup; TCAM

Access to Document

10.1109/SOCC.2016.7905446Licence: Unspecified

Feature Study on a Programmable Network Traffic Classifier
© 2016 IEEE. This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 700 KBLicence: Unspecified

Cite this

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title = "Feature Study on a Programmable Network Traffic Classifier",

abstract = "Monitoring and tracking of IP traffic flows are essential for network services (i.e. packet forwarding). Packet header lookup is the main part of flow identification by determining the predefined matching action for each incoming flow. In this paper, an improved header lookup and flow rule update solution is investigated. A detailed study of several well-known lookup algorithms reveals that searching individual packet header field and combining the results achieve high lookup speed and flexibility. The proposed hybrid lookup architecture is comprised of various lookup algorithms, which are selected based on the user applications and system requirements.",

keywords = "packet classification; multi-dimensional lookup; TCAM",

author = "{Guerra Perez}, Keissy and Xin Yang and Sandra Scott-Hayward and Sakir Sezer",

year = "2017",

month = apr,

day = "24",

doi = "10.1109/SOCC.2016.7905446",

language = "English",

isbn = "978-1-5090-1368-5",

series = "International SOC Conference (SOCC). Proceedings",

publisher = "IEEE",

pages = "108--113",

booktitle = "2016 29th IEEE International System-on-Chip Conference (SOCC): Proceedings",

note = "29th IEEE International System-on-Chip Conference, IEEE SOCC 2016 ; Conference date: 06-09-2016 Through 09-09-2016",

url = "http://www.ieee-socc.org/",

}

Guerra Perez, K, Yang, X, Scott-Hayward, S & Sezer, S 2017, Feature Study on a Programmable Network Traffic Classifier. in 2016 29th IEEE International System-on-Chip Conference (SOCC): Proceedings. International SOC Conference (SOCC). Proceedings, pp. 108-113, 29th IEEE International System-on-Chip Conference, Seattle, United States, 06/09/2016. https://doi.org/10.1109/SOCC.2016.7905446

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AU - Yang, Xin

AU - Scott-Hayward, Sandra

AU - Sezer, Sakir

PY - 2017/4/24

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N2 - Monitoring and tracking of IP traffic flows are essential for network services (i.e. packet forwarding). Packet header lookup is the main part of flow identification by determining the predefined matching action for each incoming flow. In this paper, an improved header lookup and flow rule update solution is investigated. A detailed study of several well-known lookup algorithms reveals that searching individual packet header field and combining the results achieve high lookup speed and flexibility. The proposed hybrid lookup architecture is comprised of various lookup algorithms, which are selected based on the user applications and system requirements.

AB - Monitoring and tracking of IP traffic flows are essential for network services (i.e. packet forwarding). Packet header lookup is the main part of flow identification by determining the predefined matching action for each incoming flow. In this paper, an improved header lookup and flow rule update solution is investigated. A detailed study of several well-known lookup algorithms reveals that searching individual packet header field and combining the results achieve high lookup speed and flexibility. The proposed hybrid lookup architecture is comprised of various lookup algorithms, which are selected based on the user applications and system requirements.

KW - packet classification; multi-dimensional lookup; TCAM

U2 - 10.1109/SOCC.2016.7905446

DO - 10.1109/SOCC.2016.7905446

M3 - Conference contribution

SN - 978-1-5090-1368-5

T3 - International SOC Conference (SOCC). Proceedings

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BT - 2016 29th IEEE International System-on-Chip Conference (SOCC): Proceedings

T2 - 29th IEEE International System-on-Chip Conference

Y2 - 6 September 2016 through 9 September 2016

ER -

Feature Study on a Programmable Network Traffic Classifier

Abstract

Publication series

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Keywords

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