ERFC: An Enhanced Recursive Flow Classification Algorithm

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%.