Bloom Filter (eBook)

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 influences many research fields, including Bioinformatics, Internet of Things, computer security, network appliances, Big Data and Cloud Computing. - Includes Bloom filter methods for a wide variety of applications - Defines concepts and implementation strategies that will help the reader use the suggested methods - Provides an overview of issues and challenges faced by researchers

Dr. Ripon Patgiri is an Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology Silchar, since 2013. His research interests include bloom filters, storage systems, security, and cryptography computing. He has published numerous papers in reputed journals, conferences, and books. Also, he has been awarded with several international patents. He is a senior member of IEEE. He was the General Chair of ICACNI 2018 and BigDML 2019. He is the Organizing Chair of FRSM 2020 and ADCOM 2020. Also, he is the Program Chair of CoMSO 2020, CoMSO 2021, and CoMSO 2022. He is also an editor of several multi-authored books. Moreover, he has received two research project fundings from SERB and DST, India.

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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 influences many research fields, including Bioinformatics, Internet of Things, computer security, network appliances, Big Data and Cloud Computing. - Includes Bloom filter methods for a wide variety of applications- Defines concepts and implementation strategies that will help the reader use the suggested methods- Provides an overview of issues and challenges faced by researchers