Supervised grid-of-tries: a novel framework for classifier management
ICDCN'06 Proceedings of the 8th international conference on Distributed Computing and Networking
| Hi-index | 0.00 |
Packet classification is a central function for a number of network applications, such as routing and firewalls. Most existing algorithms for packet classification scale poorly in either time or space when the databases grow in size. The scalable algorithm Aggregated Bit Vector (ABV) is an improvement on the Lucent bit vector scheme (BV), but has some limitations such as large variance in performance, rule mapping back and preprocessing cost. Our paradigm, Parallel Aggregated and Folded bit vector (PAFBV) seeks to reduce false matches while keeping the benefits of bit vector aggregation and avoiding rearrangement. This model also uses multi-ary trie structures to reduce the seek time of bit vectors and thereby increasing the speed of packet classification. The objective of this paper is to propose a scalable packet classification algorithm with increased speed for even large database size for IPv6 addresses