大方坯过滤器
计算机科学
布谷鸟搜索
网络数据包
人气
布谷鸟
滤波器(信号处理)
假阳性率
计算机网络
算法
人工智能
动物
生物
粒子群优化
社会心理学
计算机视觉
心理学
作者
Pedro Reviriego,Jorge Martínez,David Larrabeiti,Salvatore Pontarelli
出处
期刊:IEEE Transactions on Network and Service Management
[Institute of Electrical and Electronics Engineers]
日期:2020-12-01
卷期号:17 (4): 2690-2701
被引量:22
标识
DOI:10.1109/tnsm.2020.3024680
摘要
Bloom filters are used to perform approximate membership checking in a wide range of applications in both computing and networking, but the recently introduced cuckoo filter is also gaining popularity. Therefore, it is of interest to compare both filters and provide insights into their features so that designers can make an informed decision when implementing approximate membership checking in a given application. This article first compares Bloom and cuckoo filters focusing on a packet classification application. The analysis identifies a shortcoming of cuckoo filters in terms of false positive rate when they do not operate close to full occupancy. Based on that observation, this article also proposes the use of a configurable bucket to improve the scaling of the false positive rate of the cuckoo filter with occupancy.
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