电子学报2011，Vol.39Issue(4)：877-881,5.
Bloom Filters散列函数数目多阶段动态优化算法
A Multi-Stage Dynamic Optimization Algorithm for Bloom Filters Hash Functions Number
摘要
Abstract
Standard Bloom Filters needs to know the number of different elements in data set in order to determine the optimal number of hash functions. However, the data distribution information is not easy to obtain prior. This paper proposes a multistage dynamic optimization for Bloom Filters hash functions number (MDBF). It splits element insertion procedure into several stages,and in each stage of element insertion,MDBF decides the optimal hash function number by analyzing the inserted data distribution with bit vector usage situation. The experimental results show that MDBF can select the optimal number of hash functions to obtain low false positive probability in complicated applications, which have element multiplicity and skewed distribution.关键词
Bloom Filters/hash函数/偏斜分布/误检率Key words
bloom filters/ hash function/skewed distribution/ false positive probability分类
信息技术与安全科学引用本文复制引用
张伟,王汝传..Bloom Filters散列函数数目多阶段动态优化算法[J].电子学报,2011,39(4):877-881,5.基金项目
国家自然科学基金(No.60973193,61003039,61003236) （No.60973193,61003039,61003236）
江苏省自然科学基金(No.BK2008451) （No.BK2008451）
省级现代服务业发展专项基金(No.0801019C) （No.0801019C）
国家博士后基金(No.20090451241) （No.20090451241）
江苏高校科技创新计划项目(No.CX09B_153Z,CX10B_260Z,CX10B_261Z,CX10B_262Z) （No.CX09B_153Z,CX10B_260Z,CX10B_261Z,CX10B_262Z）
江苏省六大高峰人才项目(No.2008118) （No.2008118）
江苏省计算机信息处理技术重点实验室基金(2010) （2010）
