A Multi-partitioning Approach to Building Fast and Accurate Counting Bloom Filters

@article{Huang2013AMA,
  title={A Multi-partitioning Approach to Building Fast and Accurate Counting Bloom Filters},
  author={Kun Huang and Jie Zhang and Dafang Zhang and Gaogang Xie and Kav{\'e} Salamatian and Alex X. Liu and Wei Li},
  journal={2013 IEEE 27th International Symposium on Parallel and Distributed Processing},
  year={2013},
  pages={1159-1170}
}
Bloom filters are space-efficient data structures for fast set membership queries. Counting Bloom Filters (CBFs) extend Bloom filters by allowing insertions and deletions to support dynamic sets. The performance of CBFs is critical for various applications and systems. This paper presents a novel approach to building a fast and accurate data structure called Multiple-Partitioned Counting Bloom Filter (MPCBF) that addresses large-scale data processing challenges. MPCBF is based on two ideas… CONTINUE READING
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