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.
Year
DOI
Venue
2016
10.1109/SOCC.2016.7905446
2016 29th IEEE International System-on-Chip Conference (SOCC)
Keywords
Field
DocType
packet classification,multi-dimensional lookup,TCAM
Content-addressable memory,Algorithm design,Computer science,Computer network,Real-time computing,Memory management,Header,Statistical classification,Pattern matching,Packet forwarding,Internet traffic
Conference
ISBN
Citations 
PageRank 
978-1-5090-1368-5
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Keissy Guerra Perez100.34
Xin Yang2224.91
Sandra Scott-Hayward344125.28
Sakir Sezer4101084.22