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SLCF: Single-hash lookup cuckoo filter

机译:SLCF:单哈希查找杜鹃过滤器

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Approximate Membership Query (AMG) data structures are widely used in the networking area recently. The most popular AMQ data structures are Bloom, Quotient and Cuckoo Filter (CF). The CF is more efficient than the Quotient and Bloom filters in term of the lookup time and false positive rate. An issue in CF is utilization of two hash functions in the query phase that increases the lookup time. Another issue is the relocation loop problem in the programming phase that attempts to find an empty bucket for the collied items. In this paper, a new approach called Single-hash Lookup Cuckoo Filter (SLCF) using one hash function to lookup an item is proposed. In the programming phase, SLCF utilizes a sequence of hash functions without any relocation to find an empty bucket and storing the overflowed items. It finds a bucket with an empty place and sets an index in the original bucket to the address of found bucket. To accelerate the query phase, a handle as a tiny part of the fingerprint is placed in conjunction with the index value in the bucket. In the query phase, only one hash function is used and if the queried item cannot be found in the bucket, the handle is investigated to membership checking. Otherwise, the second bucket pointed by the index is accessed. The simulation results for name search in the named data networking demonstrate that the lookup time is improved 27% for 16 million names in comparison to CF.
机译:近似成员资格查询(AMG)数据结构最近在网络领域中被广泛使用。最受欢迎的AMQ数据结构是Bloom,商数和布谷鸟过滤器(CF)。就查找时间和误报率而言,CF比“商”和“布隆”滤波器更有效。 CF中的一个问题是在查询阶段使用两个哈希函数会增加查找时间。另一个问题是在编程阶段的重定位循环问题,该问题试图为被卷入的项目找到一个空桶。本文提出了一种新的方法,称为单哈希查找杜鹃过滤器(SLCF),该方法使用一个哈希函数来查找项目。在编程阶段,SLCF利用一系列哈希函数而无需任何重定位来查找空存储桶并存储溢出的项。它会找到一个空位的存储桶,并将原始存储桶中的索引设置为找到的存储桶的地址。为了加快查询阶段,将作为指纹很小一部分的句柄与存储桶中的索引值一起放置。在查询阶段,仅使用一个哈希函数,如果在存储桶中找不到所查询的项目,则将对该句柄进行成员资格检查。否则,将访问索引指向的第二个存储桶。在命名数据网络中进行名称搜索的模拟结果表明,与CF相比,1600万个名称的查找时间缩短了27%。

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