Deterministic and Efficient Hash Table Lookup Using Discriminated Vectors

Abstract

Hash table is used in many areas of networking such as route lookup, packet classification, per-flow state management and network monitoring for its constant access time latency at moderate loads. However, collisions may become frequent at high loads in traditional hash tables, which may lead the access time complexity to be linear and intolerable to applications like high-speed route lookups. While some schemes were proposed to help resolve this problem and most of them may achieve O(1) average memory access per lookup, very few of them are able to cut down the access to a deterministic single one. In this paper, we design a structure called deterministic and efficient hash table (DEHT). In DEHT, a novel data structure on on-chip memory is built, with the help of which the off-chip memory access can be decreased to a single one at most per lookup even when the load of the hash table is very high. What's more, the on-chip data structure also plays a similar role as Bloom Filter to do membership screening, which can avoid most lookups of nonexistent items of the hash table visiting the off-chip memory. Through theoretical analysis and simulations, we show that our scheme is faster than other schemes in lookup operations; the usable load of the off-chip hash table, the memory efficiency and the false positive rate of the on-chip data structure are also favorable.