Bloom Filters via d - Left Hashing and Dynamic Bit Reassignment Extended

In recent work, the authors introduced a data structure with the same functionality as a counting Bloom filter (CBF) based on fingerprints and the d-left hashing technique. This paper describes dynamic bit reassignment, an approach that allows the size of the fingerprint to flexibly change with the load in each hash bucket, thereby reducing the probability of a false positive. This technique allows us to not only improve our d-left counting Bloom filter, but also to construct a data structure with the same functionality as a Bloom filter, including the ability to handle insertions online, that yields fewer false positives for sufficiently large filters. Our results show that our d-left Bloom filter data structure begins achieving smaller false positive rates than the standard construction at 16 bits per element. We explain the technique, describe why it is amenable to hardware implementation, and provide experimental results.