Bloom Filter

Bloom Filter

A Data Structure for Computer Networking, Big Data, Cloud Computing, Internet of Things, Bioinformatics and Beyond

1st Edition - October 1, 2022

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  • Authors: Ripon Patgiri, Sabuzima Nayak, Naresh Muppalaneni
  • Paperback ISBN: 9780128235201

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Description

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. The conventional Bloom filter is a probabilistic data structure for membership filter. Burton Howard Bloom introduced an approximate membership filtering data structure in 1970. Hence, it is called a Bloom filter. Since its inception, it 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.

Key Features

  • Includes Bloom filter methods for a wide variety of applications
  • Includes concepts and implementation strategies that will help the reader to use the suggested methods
  • Provides a look at issues and challenges faced by researchers

Readership

Computer scientists, data scientists, and researchers in biomedical engineering and applied informatics students and researchers in data analytics, data science, database architects, and database management researchers and scientists

Table of Contents

  • Part I: Variants of Bloom Filter
    1. Introduction to Bloom Filter
    2. Variants of Bloom Filters
    3. Counting Bloom Filter
    4. Hierarchical Bloom Filter
    5. Multidimensional Bloom Filter
    6. High Accuracy Bloom Filter
    7. High Scalable Bloom Filter
    8. Issues and Challenges of Bloom Filters

    Part II: Applications of Bloom Filter in Networking
    9. Content-Centric Network
    10. Software-Defined Network
    11. Wireless Networking
    12. Network Security
    13. Internet of Things

    Part III: Applications of Bloom Filter in Other Domains
    14. Database and NoSQL
    15. Big Data
    16. Cloud Computing
    17. Healthcare
    18. Biometrics
    19. Bioinformatics

Product details

  • No. of pages: 232
  • Language: English
  • Copyright: © Academic Press 2022
  • Published: October 1, 2022
  • Imprint: Academic Press
  • Paperback ISBN: 9780128235201

About the Authors

Ripon Patgiri

Dr. Ripon Patgiri received his Ph.D. from the National Institute of Technology, India. He was General Chair of the 6th International Conference on Advanced Computing, Networking and Informatics, and is General Chair of International Conference on Big Data, Machine Learning and Applications. Also, he is organzing chair of the 25th International Symposium Frontiers of Research in Speech and Music and International Conference on Modeling, Simulation and Optimizations. His research interests are Bloom Filter, Machine Learning, Big Data, Networking and Distributed Computing.

Affiliations and Expertise

Assistant Professor, Department of Computer Science and Engineering, National Institute of Technology, Silchar, India

Sabuzima Nayak

Sabuzima Nayak has published numerous papers in reputed journals, conferences, and books. Her research interests include bioinformatics, Bloom Filter, Big Data, and distributed systems.

Affiliations and Expertise

Research Scholar, Department of Computer Science and Engineering, National Institute of Technology, Silchar, India

Naresh Muppalaneni

Dr. Naresh Babu Muppalaneni is the author of several books in the field of Computational Intelligence and bioinformatics, including Computational Intelligence Techniques in Diagnosis of Brain Diseases, Soft Computing and Medical Bioinformatics, Computational Intelligence in Medical Informatics, and Computational Intelligence Techniques for Comparative Genomics, all from Springer, as well as Computational Study on Protein-Ligand Interactions for Anti-Diabetic: In Silico Study from Lambert Academic Publishing He is a Senior Member of IEEE, and his research interests include Machine Learning, Computational Systems Biology, bioinformatics, Artificial Intelligence in Biomedical Engineering, applications of intelligent system techniques, image processing, and social network analysis.

Affiliations and Expertise

Assistant Professor, Department of Computer Science and Engineering, National Institute of Technology, Silchar, India

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