RocketTC: A high throughput traffic classification architecture

Zhou Zhou, Tian Song*, Wenliang Fu

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

Real-time traffic classification is becoming increasingly critical for network management, traffic engineering, and network security. Current software-based solutions, however, have difficulties dealing with a great number of flows in today's high-speed networks. This paper proposes RocketTC, a scalable FPGA-based architecture, to accelerate traffic classification while maintaining high accuracy. It combines two significant elements: (1) an efficient flow management scheme using on-chip BRAMs for storing the flow table, and (2) a parallel and pipelined classification engine array with partial dynamic reconfiguration (PDR) on FPGA. We have implemented and evaluated RocketTC on Xilinx Virtex-5 FPGA based platform. Our results show a sustained throughput of over 20 Gbps for minimum packet size of 40 bytes, and high accuracy above 97% for classifying nearly a hundred popular applications. Additionally, it is easy for RocketTC to update more application types.

源语言英语
主期刊名2012 International Conference on Computing, Networking and Communications, ICNC'12
407-411
页数5
DOI
出版状态已出版 - 2012
活动2012 International Conference on Computing, Networking and Communications, ICNC'12 - Maui, HI, 美国
期限: 30 1月 20122 2月 2012

出版系列

姓名2012 International Conference on Computing, Networking and Communications, ICNC'12

会议

会议2012 International Conference on Computing, Networking and Communications, ICNC'12
国家/地区美国
Maui, HI
时期30/01/122/02/12

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