Chapter 1: Introduction
Abstract
This book presents an in-depth analysis of Bloom Filter for diverse applications. The book explores the architectures of various Bloom Filter variants. Also, it highlights the issues, challenges, and research directions. Moreover, it presents a novel Bloom Filter, called robustBF. We experimentally demonstrate the performance of robustBF, libbloom, and Cuckoo Filter. Experimental results show that robustBF outperforms other membership filters. Furthermore, we survey the applications of Bloom Filter in diverse research domains.
Keywords
Bloom Filter; Membership filter; False positive probability; Hash function
1.1 Introduction
Bloom Filter [1] can be applied in diverse domains, namely, Big Data [2], Database [2], Cloud ...
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