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

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

Database Concurrency Control: Methods, Performance and Analysis is a review of developments in concurrency control methods for centralized database systems, with a quick digression into distributed databases and multicomputers, the emphasis being on performance. The main goals of Database Concurrency Control: Methods, Performance and Analysis are to succinctly specify various concurrency control methods; to describe models for evaluating the relative performance of concurrency control methods; to point out problem areas in earlier performance analyses; to introduce queuing network models to evaluate the baseline performance of transaction processing systems; to provide insights into the relative performance of transaction processing systems; to illustrate the application of basic analytic methods to the performance analysis of various concurrency control methods; to review transaction models which are intended to relieve the effect of lock contention; to provide guidelines for improving the performance of transaction processing systems due to concurrency control; and to point out areas for further investigation. This monograph should be of direct interest to computer scientists doing research on concurrency control methods for high performance transaction processing systems, designers of such systems, and professionals concerned with improving (tuning) the performance of transaction processing systems.

Database Concurrency Control: Methods, Performance and Analysis is a review of developments in concurrency control methods for centralized database systems, with a quick digression into distributed databases and multicomputers, the emphasis being on performance. The main goals of Database Concurrency Control: Methods, Performance and Analysis are to succinctly specify various concurrency control methods; to describe models for evaluating the relative performance of concurrency control methods; to point out problem areas in earlier performance analyses; to introduce queuing network models to evaluate the baseline performance of transaction processing systems; to provide insights into the relative performance of transaction processing systems; to illustrate the application of basic analytic methods to the performance analysis of various concurrency control methods; to review transaction models which are intended to relieve the effect of lock contention; to provide guidelines for improving the performance of transaction processing systems due to concurrency control; and to point out areas for further investigation. This monograph should be of direct interest to computer scientists doing research on concurrency control methods for high performance transaction processing systems, designers of such systems, and professionals concerned with improving (tuning) the performance of transaction processing systems.

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

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

Database Concurrency Control: Methods, Performance and Analysis is a review of developments in concurrency control methods for centralized database systems, with a quick digression into distributed databases and multicomputers, the emphasis being on performance. The main goals of Database Concurrency Control: Methods, Performance and Analysis are to succinctly specify various concurrency control methods; to describe models for evaluating the relative performance of concurrency control methods; to point out problem areas in earlier performance analyses; to introduce queuing network models to evaluate the baseline performance of transaction processing systems; to provide insights into the relative performance of transaction processing systems; to illustrate the application of basic analytic methods to the performance analysis of various concurrency control methods; to review transaction models which are intended to relieve the effect of lock contention; to provide guidelines for improving the performance of transaction processing systems due to concurrency control; and to point out areas for further investigation. This monograph should be of direct interest to computer scientists doing research on concurrency control methods for high performance transaction processing systems, designers of such systems, and professionals concerned with improving (tuning) the performance of transaction processing systems.

Database Concurrency Control: Methods, Performance and Analysis is a review of developments in concurrency control methods for centralized database systems, with a quick digression into distributed databases and multicomputers, the emphasis being on performance. The main goals of Database Concurrency Control: Methods, Performance and Analysis are to succinctly specify various concurrency control methods; to describe models for evaluating the relative performance of concurrency control methods; to point out problem areas in earlier performance analyses; to introduce queuing network models to evaluate the baseline performance of transaction processing systems; to provide insights into the relative performance of transaction processing systems; to illustrate the application of basic analytic methods to the performance analysis of various concurrency control methods; to review transaction models which are intended to relieve the effect of lock contention; to provide guidelines for improving the performance of transaction processing systems due to concurrency control; and to point out areas for further investigation. This monograph should be of direct interest to computer scientists doing research on concurrency control methods for high performance transaction processing systems, designers of such systems, and professionals concerned with improving (tuning) the performance of transaction processing systems.