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Ternary Bloom filter replacing counting Bloom filter

机译:三元Bloom过滤器代替计数Bloom过滤器

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A counting Bloom filter (CBF) generalizes a standard 1-bit vector Bloom filter and allows not only membership queries but also insertion and deletion operations for dynamic sets. However, the CBF can cause false negatives because of counter overflows. A 4-bit vector CBF, which provides the probability of false negatives sufficiently small, is generally used. However, the 4-bit vector CBF wastes memory space by allocating 4 bits for every counter, even though the half of counter values of the CBF is zero. This paper proposes a Ternary Bloom filter (TBF) which is a variation of the CBF. The TBF is motivated to use the minimum number of bits for each counter and constructs a larger Bloom filter instead. In the TBF, counters mapped with two or more number of elements are represented by X, and the counters with value X are not used in insertion, deletion, or querying operations. Since a larger Bloom filter can reference more number of counter values, the proposed TBF improves false positive rate than the CBF which consumes the same amount of memory, and the proposed TBF also removes false negative problem.
机译:计数布隆过滤器(CBF)概括了标准的1位向量布隆过滤器,不仅允许成员资格查询,还允许对动态集进行插入和删除操作。但是,由于计数器溢出,CBF可能导致假阴性。通常使用4位向量CBF,其提供足够小的假阴性概率。但是,即使CBF的计数器值的一半为零,4位向量CBF也会通过为每个计数器分配4位来浪费存储空间。本文提出了三重布鲁姆滤波器(TBF),它是CBF的一种变体。 TBF的动机是为每个计数器使用最少的位数,并构造一个更大的Bloom过滤器。在TBF中,映射有两个或更多元素的计数器用X表示,而值X的计数器不用于插入,删除或查询操作。由于较大的Bloom过滤器可以引用更多数量的计数器值,因此与消耗相同内存量的CBF相比,建议的TBF改善了误报率,并且建议的TBF还消除了误报问题。

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