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. 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
Table of Contents
Section 1 Bloom Filters1. Introduction to Bloom Filter2. Bloom Filter: A Powerful Membership Data Structure3. robustBF: A High Accuracy and Memory Efficient 2D Bloom Filter4. Impact of the Hash Functions in Bloom Filters5. Analysis on Bloom Filter: Performance, Memory and False Positive Probability6. Does not Bloom Filter bloom in Membership Filtering?7. A review on Standard Bloom Filter8. Counting Bloom Filter: Architecture and Applications9. Hierarchical Bloom FilterSection 2 Applications of Bloom Filter in Networking10. Application of Bloom Filter in Networking and Communication11. Content-Centric Network12. Software-Defined Network13. Wireless Networking14. Network SecuritySection 3 Applications of Bloom Filter in Other Domains15. Big Data16. Cloud Computing17. Biometrics18. Bioinformatics
