Storage systems : organization, performance, coding, reliability, and their data processing
Author
Published
Cambridge, MA : Morgan Kaufmann, an imprint of Elsevier, [2022].
Status
Available Online
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Format
Edition
First edition.
Language
English
ISBN
9780323908092, 0323908098, 9780323907965, 0323907962
Notes
Bibliography
Includes bibliographical references and index.
Description
Storage Systems: Organization, Performance, Coding, Reliability and Their Data Processing was motivated by the 1988 Redundant Array of Inexpensive/Independent Disks proposal to replace large form factor mainframe disks with an array of commodity disks. Disk loads are balanced by striping data into strips--with one strip per disk-- and storage reliability is enhanced via replication or erasure coding, which at best dedicates k strips per stripe to tolerate k disk failures. Flash memories have resulted in a paradigm shift with Solid State Drives (SSDs) replacing Hard Disk Drives (HDDs) for high performance applications. RAID and Flash have resulted in the emergence of new storage companies, namely EMC, NetApp, SanDisk, and Purestorage, and a multibillion-dollar storage market. Key new conferences and publications are reviewed in this book. The goal of the book is to expose students, researchers, and IT professionals to the more important developments in storage systems, while covering the evolution of storage technologies, traditional and novel databases, and novel sources of data. We describe several prototypes: FAWN at CMU, RAMCloud at Stanford, and Lightstore at MIT; Oracle's Exadata, AWS' Aurora, Alibaba's PolarDB, Fungible Data Center; and author's paper designs for cloud storage, namely heterogeneous disk arrays and hierarchical RAID. Surveys storage technologies and lists sources of data: measurements, text, audio, images, and video Familiarizes with paradigms to improve performance: caching, prefetching, log-structured file systems, and merge-trees (LSMs) Describes RAID organizations and analyzes their performance and reliability Conserves storage via data compression, deduplication, compaction, and secures data via encryption Specifies implications of storage technologies on performance and power consumption Exemplifies database parallelism for big data, analytics, deep learning via multicore CPUs, GPUs, FPGAs, and ASICs, e.g., Google's Tensor Processing Units.
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O'Reilly,O'Reilly Online Learning: Academic/Public Library Edition
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Citations
APA Citation, 7th Edition (style guide)
Thomasian, A. (2022). Storage systems: organization, performance, coding, reliability, and their data processing (First edition.). Morgan Kaufmann, an imprint of Elsevier.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Thomasian, Alexander, 1945-. 2022. Storage Systems: Organization, Performance, Coding, Reliability, and Their Data Processing. Morgan Kaufmann, an imprint of Elsevier.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Thomasian, Alexander, 1945-. Storage Systems: Organization, Performance, Coding, Reliability, and Their Data Processing Morgan Kaufmann, an imprint of Elsevier, 2022.
MLA Citation, 9th Edition (style guide)Thomasian, Alexander. Storage Systems: Organization, Performance, Coding, Reliability, and Their Data Processing First edition., Morgan Kaufmann, an imprint of Elsevier, 2022.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
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Grouped Work ID
8371574a-45a2-eaa9-0618-8235b55285df-eng
Grouping Information
| Grouped Work ID | 8371574a-45a2-eaa9-0618-8235b55285df-eng |
|---|---|
| Full title | storage systems organization performance coding reliability and their data processing |
| Author | thomasian alexander |
| Grouping Category | book |
| Last Update | 2024-10-08 10:55:34AM |
| Last Indexed | 2024-11-08 03:23:08AM |
Book Cover Information
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| 505 | 0 | |a 1. Introduction 2. Storage Technologies and Their Data 3. Disk Drive Data Placement and Scheduling 4. Mirrored & Hybrid Arrays 5. Redundant Arrays of Independent Disks -- RAID 6. Coding for Multiple Disk Failures 7. Saving Power in Disks, Flash Memories, and Servers 8. Database Parallelism, Big Data and Analytics, Deep Learning 9. Structured, Unstructured, and Diverse Databases 10. Heterogeneous Disk Arrays -- HDAs 11. Hierarchical RAID -- HRAID 12. Conclusions Appendix</p> | |
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