Feature Study on a Programmable Network Traffic Classifier

被引：0

作者：

Perez, Keissy Guerra ^{[1
]}

Yang, Xin ^{[1
]}

Scott-Hayward, Sandra ^{[1
]}

Sezer, Sakir ^{[1
]}

机构：

[1] Queens Univ Belfast, ECIT Inst, Belfast, Antrim, North Ireland

来源：

2016 29TH IEEE INTERNATIONAL SYSTEM-ON-CHIP CONFERENCE (SOCC) | 2016年

基金：

英国工程与自然科学研究理事会;

关键词：

packet classification; multi-dimensional lookup; TCAM;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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 arc selected based on the user applications and system requirements.

引用

页码：108 / 113

页数：6

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