Название: Bloom Filter: A Data Structure for Computer Networking, Big Data, Cloud Computing, Internet of Things, Bioinformatics and Beyond
Автор: Ripon Patgiri, Sabuzima Nayak, Naresh Babu Muppalaneni
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 230
Язык: английский
Формат: pdf (true), epub
Размер: 18.3 MB

Bloom Filter: A Data Structure for Computer Networking, Big Data, Cloud Computing, Internet of Things, Bioinformatics, and Beyond focuses on both the theory and practice of the most emerging areas for Bloom filter application, including Big Data, Cloud Computing, Internet of Things, and Bioinformatics. Sections provide in-depth insights on structure and variants, focus on its role in computer networking, and discuss applications in various research domains, such as Big Data, Cloud Computing, and Bioinformatics. Since its inception, the Bloom Filter has been extensively experimented with and developed to enhance system performance such as web cache.

Bloom Filter is a simple data structure for membership filtering. It has a simple architecture and operations with high performance. The input items are mapped to the Bloom Filter rather than storage. This feature of Bloom Filter is both a blessing and a curse. A blessing because it has a low memory footprint and fast operation. A curse because it is not a standalone technique, rather a system/application enhancer. A big data application or an application responsible for processing a huge volume of data can implement Bloom Filter to enhance its processing performance. Bloom Filter with constant time complexity operation processes the incoming item quickly, specifically it has great advantage where the application has more negative responses. In case Bloom Filter returns “false”, the item is definitely absent; otherwise if Bloom Filter returns “true”, an item may be present in the application.

The simple Bloom Filter is a versatile data structure. It can be implemented in diverse applications. We, the authors, wrote some review papers to highlight the role of Bloom Filter, its issue and challenges in some areas. Then we realized that the research world does not need a review paper on Bloom Filter, but rather a book to illustrate the diverse applications of Bloom Filter. In the book we tried to advocate the superiority of Bloom Filter.

Bloom filter influences many research fields, including Bioinformatics, Internet of Things, computer security, network appliances, Big Data and Cloud Computing.