Field-trimming Compression Model for Rule Set of Packet Classification

SUN Penghao; LAN Julong; LU Xiaoyuan; HU Yuxiang; MA Teng

doi:10.11999/JEIT160740

Volume 39 Issue 5

May 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(5): 1185-1192

SUN Penghao, LAN Julong, LU Xiaoyuan, HU Yuxiang, MA Teng. Field-trimming Compression Model for Rule Set of Packet Classification[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1185-1192. doi: 10.11999/JEIT160740

Citation:

SUN Penghao, LAN Julong, LU Xiaoyuan, HU Yuxiang, MA Teng. Field-trimming Compression Model for Rule Set of Packet Classification[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1185-1192. doi: 10.11999/JEIT160740

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Field-trimming Compression Model for Rule Set of Packet Classification

doi: 10.11999/JEIT160740

1.
(National Digital Switching System Engineering &
2.
(Shanghai Engineering Research Center for Broadband Technologies &

Funds:

The National 973 Program of China (2012CB315901), The National Natural Science Foundation of China (61521003), The National 863 Program of China (2013AA013505)

Received Date: 2016-07-11
Rev Recd Date: 2017-02-08
Publish Date: 2017-05-19

Abstract

Abstract

With the emergence of multi-field packet classification such as OpenFlow, the increasing number of match fields, continuous growth in bit-width of entries and ever growing scale of rule set all bring much pressure on the storage space in hardware. To improve the utilization of the existing Ternary Content Addressable Memory (TCAM) resources, a match field reduction scheme Field Trimmer is proposed based on the analysis of rule feature. On the one hand, with the analysis of logical relationships among different match fields, some fields can be merged to reduce the number of match fields. On the other hand, with the analysis of statistical features in a rule set, some of the match fields are picked up to achieve the classification function of the whole set. Experiment result shows that with less algorithm complexity, the proposed scheme can save around 50% storage space in the rule set of OpenFlow compared to the best prior art, and about 40% storage space in the popular 5-tuple packet classification rule set.
- Packet classification,
- Ternary Content Addressable Memory (TCAM),
- OpenFlow

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References(21)

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