Название: Storage Systems: Organization, Performance, Coding, Reliability, and Their Data ProcessingАвтор: Alexander Thomasian
Издательство: Morgan Kaufmann/Elsevier
Год: 2022
Страниц: 748
Язык: английский
Формат: pdf (true), epub
Размер: 11.3 MB, 10.2 MB
Storage Systems: Organization, Performance, Coding, Reliability and Their Data Processing covers the coding, reliability and performance of popular RAID organizations: RAID1 mirrored disks, RAID5/6/7 1/2/3-disk failure tolerant - 1/2/3DFT arrays. Readers will learn about the storage of files, SQL and NoSQL databases on disk and SSD to achieve higher efficiency. As data compression, deduplication and encryption techniques for storage systems have led to new technologies, startups and techniques to save power in storage and server systems, the book discusses Fast Array of Wimpy Nodes (FAWN) at CMU, RAMCloud at Stanford, and key-value flash Lightstore at MIT, along with several storage proposals.
Finally, storage technologies from punched cards up to ash memories and beyond are discussed, along with the data placement and the scheduling of magnetic disks.
Provides readers with an in-depth understanding of the architecture and operation of computer storage systems
Includes descriptions of various RAID levels, their coding, organization, performance and reliability
Covers techniques for efficient and secure data storage through data compression, deduplication and encryption
Presents readers with an in-depth understanding of the storage of files and SQL and NoSQL databases
Intended audience and required background to read the book:
The book is intended for students in computer science and engineering, electrical and industrial engineering, management information sciences, information science and technology students. IT professionals may benefit from reading this book to broaden their horizon. Readers exposed to Wintel (Windows on Intel processors) versions of UNIX, and Apple computers will benefit from learning about the variety of computers, including the latest developments.
The reader should preferably have background in basic computer science and mathematics (discrete math, probability, and Markov chains), but may skip sections requiring such background which he/she finds difficult. Readers are encouraged to refer to the original material for details and illustrations.
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