Optimizing data popularity conscious bloom filters

Proceedings of the Annual ACM Symposium on Principles of Distributed Computing

Volumn , Issue , 2008, Pages 355-364

  Zhong, Ming ^a,c   Lu, Pin ^b   Shen, Kai ^b   Seiferas, Joel ^b  

^a GOOGLE INC   (United States)

^b University of Rochester

^c UNIVERSITY OF ROCHESTER   (United States)

Author keywords

Bloom filters; Dynamic programming; Knapsack problems; Optimization

Indexed keywords

APPROXIMATION ALGORITHMS; COMBINATORIAL OPTIMIZATION; DATA STRUCTURES; DISTRIBUTED COMPUTER SYSTEMS; DYNAMIC PROGRAMMING; INTEGER PROGRAMMING; OPTIMIZATION; POLYNOMIAL APPROXIMATION; PROBABILITY;

APPROXIMATION RATIOS; BLOOM FILTERS; DISTRIBUTED APPLICATIONS; KNAPSACK PROBLEMS; NONLINEAR INTEGER PROGRAM; QUANTITATIVE EVALUATION; SET MEMBERSHIP QUERY; SKEWED DISTRIBUTION;

C (PROGRAMMING LANGUAGE);

EID: 57549111038     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1400751.1400798     Document Type: Conference Paper

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