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ERFC: An Enhanced Recursive Flow Classification Algorithm

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Abstract

Packet classification on multi-fields is a fundamental mechanism in network equipments, and various classification solutions have been proposed. Because of inherent difficulties, many of these solutions scale poorly in either time or space as rule sets grow in size. Recursive Flow Classification (RFC) is an algorithm with a very high classifying speed. However, its preprocessing complexity and memory requirement are rather high. In this paper, we propose an enhanced RFC (ERFC) algorithm, in which a hash-based aggregated bit vector scheme is exploited to speed up its preprocessing procedure. A compressed and cacheable data structure is also introduced to decrease total memory requirement and improve its searching performance. Evaluation results show that ERFC provides a great improvement over RFC in both space requirement and preprocessing time. The search time complexity of ERFC is equivalent to that of RFC in the worst case; and its average classifying speed is improved by about 100%.

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Authors and Affiliations

  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Xiang-Yang Gong, Wen-Dong Wang (Senior Member, CCF) & Shi-Duan Cheng

Authors
  1. Xiang-Yang Gong
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  2. Wen-Dong Wang
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  3. Shi-Duan Cheng
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Corresponding author

Correspondence to Xiang-Yang Gong.

Additional information

Supported by the National Basic Research 973 Program of China under Grant No. 2009CB320504 and the National Hi-Tech Research and Development 863 Program of China under Grant Nos. 2008AA01A324 and 2009AA01Z210.

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Gong, XY., Wang, WD. & Cheng, SD. ERFC: An Enhanced Recursive Flow Classification Algorithm. J. Comput. Sci. Technol. 25, 958–969 (2010). https://doi.org/10.1007/s11390-010-9380-7

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  • DOI: https://doi.org/10.1007/s11390-010-9380-7

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