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In the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage. Duplicated data or redundant data is a main challenge in the field of data science research. Data Deduplication Approaches: Concepts, Strategies, and Challenges shows readers the various methods that can be used to eliminate multiple copies of the same files as well as duplicated segments or chunks of data within the associated files. Due to ever-increasing data duplication, its deduplication has become an especially useful field of research for storage environments, in particular persistent data storage. Data Deduplication Approaches provides readers with an overview of the concepts and background of data deduplication approaches, then proceeds to demonstrate in technical detail the strategies and challenges of real-time implementations of handling big data, data science, data backup, and recovery. The book also includes future research directions, case studies, and real-world applications of data deduplication, focusing on reduced storage, backup, recovery, and reliability.
- Includes data deduplication methods for a wide variety of applications
- Includes concepts and implementation strategies that will help the reader to use the suggested methods
- Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable methods for their applications
- Focuses on reduced storage, backup, recovery, and reliability, which are the most important aspects of implementing data deduplication approaches
- Includes case studies
Biomedical Engineers and researchers in biomedical engineering, applied informatics, and data science
students and researchers in artificial intelligence, data analytics, and data science
- Introduction to data deduplication approaches
2. Data deduplication concepts
3. Concepts, strategies, and challenges of data deduplication
4. Existing mechanisms for data deduplication
5. Classification criteria for data deduplication methods
6. File chunking approaches
7. Study of data deduplication for file chunking approaches
8. Essentials of data deduplication using open-source toolkit
9. Efficient data deduplication scheme for scale-out distributed storage
10. Identification of duplicate bug reports in software bug repositories: a systematic review, challenges and future scope
11. A survey and critical analysis on energy generation from datacenter
12. Review of MODIS EVI and NDVI data for data mining applications
13. Performance modeling for secure migration processes of legacy systems to the cloud computing
14. DedupCloud: an optimized efficient virtual machine deduplication algorithm in cloud computing environment
15. Data deduplication for cloud storage
16. Data duplication using Amazon Web Services cloud storage
17. Game-theoretic analysis of encrypted cloud data deduplication
18. Data deduplication applications in cognitive science and computer vision research
- No. of pages:
- © Academic Press 2020
- 25th November 2020
- Academic Press
- Paperback ISBN:
- eBook ISBN:
Tin Thein Thwel, PhD is a Professor at Myanmar Institute of Information Technology (MIIT), Mandalay, Myanmar. She received her PhD in Information Technology from the University of Computer Studies, Yangon (UCSY), Myanmar. She is a reviewer and technical committee member of the International Conference on Computer and Applications (ICCA) on data deduplication, cyber security, data mining, and information retrieval. She has 16 years of teaching experience at the university level and her research interests include data deduplication, cyber security, data mining and data science, information retrieval, and distributed computing.
Professor, Myanmar Institute of Information Technology (MIIT), Mandalay, Myanmar
G. R. Sinha, PhD is an Adjunct Professor at International Institute of Information Technology (IIIT) Bangalore, India, and presently deputed as Professor at Myanmar Institute of Information Technology (MIIT), Mandalay, Myanmar. He has published 259 research papers in various international and national journals and conferences. He has edited four books with Elsevier, Springer and IOP; and currently editing seven more books with reputed publishers. He is a Visiting Professor (Honorary) of Sri Lanka Technological Campus Colombo. He is a Senate member of MIIT and also ACM Distinguished Speaker in the field of Digital Signal Processing. His research areas include cognitive science, brain computing, image processing, and data science applications.
Adjunct Professor, International Institute of Information Technology (IIIT), Bangalore, India
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