Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others.
The material is organized according to the system model—first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference.
The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms—to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.
About the author: Nancy A. Lynch is a professor of electrical engineering and computer science at MIT and heads MIT's Theory of Distributed Systems research group. She is the author of numerous research articles about distributed algorithms and impossibility results, and about formal modeling and verification of distributed systems.
A basic knowledge of GNU/Linux, and storage systems, and server components is assumed. If you have no experience of software-defined storage solutions and Ceph, but are eager to learn about them, this is the book for you.What You Will LearnThe limitations of existing systems and why you should use Ceph as a storage solutionFamiliarity with Ceph's architecture, components, and servicesInstant deployment and testing of Ceph within a Vagrant and VirtualBox environmentCeph operations including maintenance, monitoring, and troubleshootingStorage provisioning of Ceph's block, object, and filesystem servicesIntegrate Ceph with OpenStackAdvanced topics including erasure coding, CRUSH maps, and performance tuningBest practices for your Ceph clustersIn Detail
Learning Ceph, Second Edition will give you all the skills you need to plan, deploy, and effectively manage your Ceph cluster. You will begin with the first module, where you will be introduced to Ceph use cases, its architecture, and core projects. In the next module, you will learn to set up a test cluster, using Ceph clusters and hardware selection. After you have learned to use Ceph clusters, the next module will teach you how to monitor cluster health, improve performance, and troubleshoot any issues that arise. In the last module, you will learn to integrate Ceph with other tools such as OpenStack, Glance, Manila, Swift, and Cinder.
By the end of the book you will have learned to use Ceph effectively for your data storage requirements.Style and approach
This step-by-step guide, including use cases and examples, not only helps you to easily use Ceph but also demonstrates how you can use it to solve any of your server or drive storage issues.
This IBM Redbooks® publication reviews the best practices for anyone who is implementing VMware® vSphere with N series unified storage arrays.
The book is divided into 11 chapters, which cover the following:Overview of transaction processing application and system structureSoftware abstractions found in transaction processing systemsArchitecture of multitier applications and the functions of transactional middleware and database serversQueued transaction processing and its internals, with IBM's Websphere MQ and Oracle's Stream AQ as examplesBusiness process management and its mechanismsDescription of the two-phase locking function, B-tree locking and multigranularity locking used in SQL database systems and nested transaction lockingSystem recovery and its failuresTwo-phase commit protocolComparison between the tradeoffs of replicating servers versus replication resourcesTransactional middleware products and standardsFuture trends, such as cloud computing platforms, composing scalable systems using distributed computing components, the use of flash storage to replace disks and data streams from sensor devices as a source of transaction requests.
The text meets the needs of systems professionals, such as IT application programmers who construct TP applications, application analysts, and product developers. The book will also be invaluable to students and novices in application programming.Complete revision of the classic "non mathematical" transaction processing reference for systems professionals. Updated to focus on the needs of transaction processing via the Internet-- the main focus of business data processing investments, via web application servers, SOA, and important new TP standards. Retains the practical, non-mathematical, but thorough conceptual basis of the first edition.
The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool.
This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling.Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templatesDevelops ideas for creating consistent approaches to high quality data models
This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises.
This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective.Thorough coverage of the fundamentals and relevant theoryRecognition and support for the creative side of the processExpanded coverage of applied data modeling includes new chapters on logical and physical database designNew material describing a powerful technique for model verificationUnique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict