On Reducing False Positives of a Bloom Filter in Trie-Based Algorithms

Many IP address lookup approaches employ Bloom filters to obtain a high-speed search performance. Especially, it has been recently studied that the search performance of trie-based algorithms can be significantly improved by adding Bloom filters. In such algorithms, the number of trie accesses can be greatly reduced because Bloom filters can determine whether a node exists in a trie without actually accessing the trie. Bloom filters do not have false negatives but have false positives. False positives can lead to unnecessary trie accesses. The false positive rate must thus be reduced to enhance the performance of lookup algorithms applying Bloom filters. One important characteristic of trie-based algorithms is that all the ancestors of a node are also stored. The proposed algorithm utilizes this characteristic in reducing the false positive rate of a Bloom filter without increasing the size of the memory for the Bloom filter. When a Bloom filter produces a positive result for a node of a trie, we propose to check whether the ancestors of the node are also positives. Because Bloom filters have no false negatives, the negatives of any of the ancestors mean that the positive of the node is false. In other words, we propose to use more Bloom filter queries to reduce the false positive rate of a Bloom filter in trie-based algorithms. Simulation results show that querying one ancestor of a node can reduce the false positive rate by up to 67% with exactly the same architecture and the same memory requirement. The proposed approach can be applied to other trie-based algorithms employing Bloom filters.