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

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.

Table of Contents:
Section 1 Bloom Filters 1. Introduction to Bloom Filter 2. Bloom Filter: A Powerful Membership Data Structure 3. robustBF: A High Accuracy and Memory Efficient 2D Bloom Filter 4. Impact of the Hash Functions in Bloom Filters 5. Analysis on Bloom Filter: Performance, Memory and False Positive Probability 6. Does not Bloom Filter bloom in Membership Filtering? 7. A review on Standard Bloom Filter 8. Counting Bloom Filter: Architecture and Applications 9. Hierarchical Bloom Filter Section 2 Applications of Bloom Filter in Networking 10. Application of Bloom Filter in Networking and Communication 11. Content-Centric Network 12. Software-Defined Network 13. Wireless Networking 14. Network Security Section 3 Applications of Bloom Filter in Other Domains 15. Big Data 16. Cloud Computing 17. Biometrics 18. Bioinformatics

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