high-speed packet classification using binary search on length
Packet classification is one of the major challenges for next generation routers since it involves complicated multi-dimensional search as well as it should be performed in wire-speed for all incoming packets. Area-based quad-trie is an excellent algorithm in the sense that it constructs a two-dimensional trie using source and destination prefix fields for packet classification. However, it does not achieve good search performance since search is linearly performed for prefix length. In this paper, we propose a new packet classification algorithm which applies binary search on prefix length to the area-based quad-trie. In order to avoid the pre-computation required in the binary search on length, the proposed algorithm constructs multiple disjoint tries depending on relative levels in rule hierarchy. We also propose two new optimization techniques considering rule priorities. For different types of rule sets having about 5000 rules, performance evaluation result shows that the average number of memory accesses is 18 to 67 and the memory consumption is 22 to 41 bytes per rule.
packet classification binary search on length area-based quad-trie best matching rule hashing