Fei Hu - Big Data: Storage Sharing and Security [2016, PDF, ENG]

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Post 31-Jul-2018 17:29

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Big Data: Storage Sharing and Security
[img=right]https://img11.lostpic.net/2018/07/27/e6c89c99cfdc15...ad6.th.png[/img]
Год издания: 2016
Автор: Fei Hu
Издательство: CRC Press
ISBN: 9781498734868
Язык: Английский
Формат файла: PDF
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 463
Описание:
Although there are already some books published on Big Data, most of them only cover basic concepts and society impacts and ignore the internal implementation details—making them unsuitable to R&D people. To fill such a need, Big Data: Storage, Sharing, and Security examines Big Data management from an R&D perspective. It covers the 3S designs—storage, sharing, and security—through detailed descriptions of Big Data concepts and implementations.
Written by well-recognized Big Data experts around the world, the book contains more than 450 pages of technical details on the most important implementation aspects regarding Big Data. After reading this book, you will understand how to:
  • Aggregate heterogeneous types of data from numerous sources, and then use efficient database management technology to store the Big Data
  • Use cloud computing to share the Big Data among large groups of people
  • Protect the privacy of Big Data during network sharing
With the goal of facilitating the scientific research and engineering design of Big Data systems, the book consists of two parts. Part I, Big Data Management, addresses the important topics of spatial management, data transfer, and data processing. Part II, Security and Privacy Issues, provides technical details on security, privacy, and accountability.
Examining the state of the art of Big Data over clouds, the book presents a novel architecture for achieving reliability, availability, and security for services running on the clouds. It supplies technical descriptions of Big Data models, algorithms, and implementations, and considers the emerging developments in Big Data applications. Each chapter includes references for further study.


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