How Cuckoo Filter Can Improve Existing Approximate Matching Techniques
نویسندگان
چکیده
منابع مشابه
A Cuckoo Filter Modification Inspired by Bloom Filter
Probabilistic data structures are so popular in membership queries, network applications, and so on. Bloom Filter and Cuckoo Filter are two popular space efficient models that incorporate in set membership checking part of many important protocols. They are compact representation of data that use hash functions to randomize a set of items. Being able to store more elements while keeping a reaso...
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The cuckoo filter data structure of Fan, Andersen, Kaminsky, and Mitzenmacher (CoNEXT 2014) performs the same approximate set operations as a Bloom filter in less memory, with better locality of reference, and adds the ability to delete elements as well as to insert them. However, until now it has lacked theoretical guarantees on its performance. We describe a simplified version of the cuckoo f...
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We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that extends cuckoo filters by reacting to false positives, removing them for future queries. As an example application, in packet processing queries may correspond to flow identifiers, so a search for an element is likely to be followed by repeated searches for that element. Removing false positives ...
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a r t i c l e i n f o a b s t r a c t Bloom filters (BFs) are used in many applications for approximate check of set membership. Counting Bloom filters (CBFs) are an extension of BFs that enable the deletion of entries at the cost of additional storage requirements. Several alternatives to CBFs can be used to reduce the storage overhead. For example schemes based on d-left hashing or Cuckoo has...
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