12 Facts About Bloom filter

Bloom filter is a space-efficient probabilistic data structure, conceived by Burton Howard Bloom in 1970, that is used to test whether an element is a member of a set.

An empty Bloom filter is a bit array of bits, all set to 0.

One-time removal of an element from a Bloom filter can be simulated by having a second Bloom filter that contains items that have been removed.

However, if the number of potential values is small and many of them can be in the set, the Bloom filter is easily surpassed by the deterministic bit array, which requires only one bit for each potential element.

The generalized Bloom filter allows many more bits to be set while still maintaining a low false positive rate; if the parameters are chosen well, about half of the bits will be set, and these will be apparently random, minimizing redundancy and maximizing information content.

Where is an estimate of the number of items in the Bloom filter, m is the length of the Bloom filter, k is the number of hash functions, and X is the number of bits set to one.

Kiss et al described a new construction for the Bloom filter that avoids false positives in addition to the typical non-existence of false negatives.

Unlike the typical Bloom filter, elements are hashed to a bit array through deterministic, fast and simple-to-calculate functions.

One of the main obstacles for a parallel Bloom filter is the organization and communication of the unordered data which is, in general, distributed evenly over all PEs at the initiation or at batch insertions.

For both approaches a "Single Shot" Bloom filter is used which only calculates one hash, resulting in one flipped bit per element, to reduce the communication volume.

Golomb coding each bloom filter is sent as packet to the PE responsible for the hash values that where inserted into it.

The regular or local Bloom filter indicates which services are offered by the node itself.