Organizations today depend heavily on their data. Even short periods of data outages can be expensive and result in loss of productivity, as well as financial consequences, while permanent data loss can be catastrophic. Therefore, reliability and means to efficiently store and access such data is an important component of most large organizations' IT infrastructure. Much of this data is still stored in the most versatile format, the 'flat file'. This eBook provides both an academic and historic perspective on the development of distributed file systems and details some of the core algorithms, such as quorum protocols that are used in distributed storage systems. This book can be used as a short, stand-alone introduction to the field or as a resource for an academic course in the topic.
What Is Distributed Ledger A distributed ledger is a database that is consensually shared and synchronized across multiple sites, institutions, or geographies, accessible by multiple people. It allows transactions to have public "witnesses." The participant at each node of the network can access the recordings shared across that network and can own an identical copy of it. Any changes, or additions, made to the ledger, are reflected, and copied to all participants in a matter of seconds or minutes. Blockchain is using the underlying technology of distributed ledgers. Bitcoin is using the underlying technology of Blockchain. Blockchain is a type of distributed ledger used by bitcoin. Blockchain is the latest buzz words in the market. Bitcoin is great, but the potential of the underlying technology is immense. Something that started as an evolution is soon going to cause a revolution. Investors are cashing in huge amount because they understand the fortune of this ingenious technology is very bright. Industry experts and tech enthusiasts are producing blockchain-based products every next day. So, wait not, and get industry-ready with this book which will describe distributed ledger in depth. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Distributed Ledger Chapter 2: Hyperledger Chapter 3: Confidential Consortium Framework Chapter 4: Eventual Consistency Chapter 5: ACID Chapter 6: CAP Theorem Chapter 7: Concurrency Control Chapter 8: Jakarta Transactions Chapter 9: Transactional NTFS Chapter 10: Two Phase Commit Protocol Chapter 11: CRUD Chapter 12: OSI Model (II) Answering the public top questions about distributed ledger. (III) Real world examples for the usage of distributed ledger in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technology in each industry to have 360-degree full understanding of distributed ledger' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of distributed ledger.
This book examines the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view. Internet of Things and Data Analytics Handbook describes essential technical knowledge, building blocks, processes, design principles, implementation, and marketing for IoT projects. It provides readers with knowledge in planning, designing, and implementing IoT projects. The book is written by experts on the subject matter, including international experts from nine countries in the consumer and enterprise fields of IoT. The text starts with an overview and anatomy of IoT, ecosystem of IoT, communication protocols, networking, and available hardware, both present and future applications and transformations, and business models. The text also addresses big data analytics, machine learning, cloud computing, and consideration of sustainability that are essential to be both socially responsible and successful. Design and implementation processes are illustrated with best practices and case studies in action. In addition, the book: Examines cloud computing, data analytics, and sustainability and how they relate to IoT overs the scope of consumer, government, and enterprise applications Includes best practices, business model, and real-world case studies Hwaiyu Geng, P.E., is a consultant with Amica Research (www.AmicaResearch.org, Palo Alto, California), promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, Hewlett Packard, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at international conferences. Mr. Geng, a patent holder, is also the editor/author of Data Center Handbook (Wiley, 2015).
When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
In modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Guerraoui and Rodrigues present an introductory description of fundamental reliable distributed programming abstractions as well as algorithms to implement these abstractions. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one specific class of abstractions, covering reliable delivery, shared memory, consensus and various forms of agreement. This textbook comes with a companion set of running examples implemented in Java. These can be used by students to get a better understanding of how reliable distributed programming abstractions can be implemented and used in practice. Combined, the chapters deliver a full course on reliable distributed programming. The book can also be used as a complete reference on the basic elements required to build reliable distributed applications.
Learning to build distributed systems is hard, especially if they are large scale. It's not that there is a lack of information out there. You can find academic papers, engineering blogs, and even books on the subject. The problem is that the available information is spread out all over the place, and if you were to put it on a spectrum from theory to practice, you would find a lot of material at the two ends but not much in the middle. That is why I decided to write a book that brings together the core theoretical and practical concepts of distributed systems so that you don't have to spend hours connecting the dots. This book will guide you through the fundamentals of large-scale distributed systems, with just enough details and external references to dive deeper. This is the guide I wished existed when I first started out, based on my experience building large distributed systems that scale to millions of requests per second and billions of devices. If you are a developer working on the backend of web or mobile applications (or would like to be!), this book is for you. When building distributed applications, you need to be familiar with the network stack, data consistency models, scalability and reliability patterns, observability best practices, and much more. Although you can build applications without knowing much of that, you will end up spending hours debugging and re-architecting them, learning hard lessons that you could have acquired in a much faster and less painful way. However, if you have several years of experience designing and building highly available and fault-tolerant applications that scale to millions of users, this book might not be for you. As an expert, you are likely looking for depth rather than breadth, and this book focuses more on the latter since it would be impossible to cover the field otherwise. The second edition is a complete rewrite of the previous edition. Every page of the first edition has been reviewed and where appropriate reworked, with new topics covered for the first time.
This book constitutes the thoroughly refereed proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015, held in Lisbon, Portugal, in November 2015. The 25 full papers presented together with 2 invited papers were carefully reviewed and selected from 280 submissions. The papers are organized in topical sections on knowledge discovery and information retrieval; knowledge engineering and ontology development; and knowledge management and information sharing.
This book presents a comprehensive review of key distributed graph algorithms for computer network applications, with a particular emphasis on practical implementation. Topics and features: introduces a range of fundamental graph algorithms, covering spanning trees, graph traversal algorithms, routing algorithms, and self-stabilization; reviews graph-theoretical distributed approximation algorithms with applications in ad hoc wireless networks; describes in detail the implementation of each algorithm, with extensive use of supporting examples, and discusses their concrete network applications; examines key graph-theoretical algorithm concepts, such as dominating sets, and parameters for mobility and energy levels of nodes in wireless ad hoc networks, and provides a contemporary survey of each topic; presents a simple simulator, developed to run distributed algorithms; provides practical exercises at the end of each chapter.
Distributed computing is at the heart of many applications. It arises as soon as one has to solve a problem in terms of entities -- such as processes, peers, processors, nodes, or agents -- that individually have only a partial knowledge of the many input parameters associated with the problem. In particular each entity cooperating towards the common goal cannot have an instantaneous knowledge of the current state of the other entities. Whereas parallel computing is mainly concerned with 'efficiency', and real-time computing is mainly concerned with 'on-time computing', distributed computing is mainly concerned with 'mastering uncertainty' created by issues such as the multiplicity of control flows, asynchronous communication, unstable behaviors, mobility, and dynamicity. While some distributed algorithms consist of a few lines only, their behavior can be difficult to understand and their properties hard to state and prove. The aim of this book is to present in a comprehensive way the basic notions, concepts, and algorithms of distributed computing when the distributed entities cooperate by sending and receiving messages on top of an asynchronous network. The book is composed of seventeen chapters structured into six parts: distributed graph algorithms, in particular what makes them different from sequential or parallel algorithms; logical time and global states, the core of the book; mutual exclusion and resource allocation; high-level communication abstractions; distributed detection of properties; and distributed shared memory. The author establishes clear objectives per chapter and the content is supported throughout with illustrative examples, summaries, exercises, and annotated bibliographies. This book constitutes an introduction to distributed computing and is suitable for advanced undergraduate students or graduate students in computer science and computer engineering, graduate students in mathematics interested in distributed computing, and practitioners and engineers involved in the design and implementation of distributed applications. The reader should have a basic knowledge of algorithms and operating systems.
The book presents comprehensive coverage of Computer Graphics and Multimedia concepts in a simple, lucid and systematic way. It uses C programming language to implement various algorithms explained in the book. The book is divided into two parts. The first part focuses on a wide range of exciting topics such as illumination and colour models, shading algorithms, line, curves, circle and ellipse drawing algorithms, polygon filling, 2D and 3D transformations, windowing and clipping, 3D object representation, 3D viewing, viewing pipeline, and visible surface detection algorithms. The second part focuses on multimedia basics, multimedia applications, multimedia system architecture, evolving technologies for multimedia, defining objects for multimedia systems, multimedia data interface standards, multimedia databases, compression and decompression, data and file format standards, multimedia I/O technologies, digital voice and audio, video image and animation, full-motion video and storage and retrieval technologies. It also describes multimedia authoring and user interface, Hypermedia messaging, mobile messaging, integrated multimedia message standards, integrated document management and distributed multimedia systems. Case Study : Blender graphics - Blender fundamentals, drawing basic shapes, modelling, shading and textures.
