A hash-based scalable IP lookup using Bloom and fingerprint filters

Several challenges in the IP lookup architecture must be addressed for a high-speed forwarding in a large scale routing table: power, memory, and lookup complexity. Hash-based architectures have lookup schemes that are recognized for being both power and memory efficient due to their O(1) lookup, in contrast to other contemporary architectures. In this paper, we propose a novel hash architecture to address these issues by using pipelined Bloom and fingerprint filters for a binary searching in keys. The proposed hash scheme encodes keys' indexes to an on-chip fingerprint table, approximately returns a few indexes in a key query without pointer overhead, and makes a perfect match in an off-chip key table. Due to a memory banking system in pipeline stages, we can achieve O(1) pipelined throughput complexity of insertion, deletion, and query operations. For the IP lookup, a Lulea bitmap with our hash scheme supports a prefix lookup without inflating the numbers of prefixes and next-hops, so that our scalable hash-based scheme can achieve the worst case O(1) IP lookup. The simulation with large scale routing tables shows that our IP lookup scheme offers 4.5 and 50.1 times memory and power efficiencies than other contemporary hash and TCAM schemes, respectively.