Big Data Platforms and Applications Case Studies, Methods, Techniques, and Performance Evaluation
Language: English
Published by Palgrave Macmillan, 2021
Series: Book 45 of 45 - Computer Communications and Networks
- Hardcover
- New
Condition: New
£ 195.58
Quantity: 2 available
Add to basketItem description from seller
This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge.The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are neededfor real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service. Sprache: Englisch Gewicht in Gramm: 577.…
Seller Inventory # IB-1206487
- Title
- Big Data Platforms and Applications Case Studies, Methods, Techniques, and Performance Evaluation
- Publisher
- Palgrave Macmillan
- Publication year
- 2021
- Condition
- Neu
- Binding
- Gebundene Ausgabe
- Language
- English
- ISBN 10
- 3030388352
- ISBN 13
- 9783030388355
- Item weight
- 577 grams
- Series
- Book 45 of 45: Computer Communications and Networks
This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation.
The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge.
The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are neededfor real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Florin Pop is a Professor at the Department of Computer Science and Engineering at the University Politehnica of Bucharest, Romania and a Senior Researcher (1st Degree) at the Department of Intelligent and Distributed Data Intensive Systems at the National Institute for Research and Development in Informatics, Bucharest, Romania.
Dr. Gabriel Neagu is a Senior Researcher (1st Degree) at the Department of Intelligent and Distributed Data Intensive Systems at the National Institute for Research and Development in Informatics, Bucharest, Romania.
"About the title" may belong to another edition of this title.
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