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This book presents the most important fault-tolerant distributed programming abstractions and their associated distributed algorithms, in particular in terms of reliable communication and agreement, which lie at the heart of nearly all distributed applications. These programming abstractions, distributed objects or services, allow software designers and programmers to cope with asynchrony and the most important types of failures such as process crashes, message losses, and malicious behaviors of computing entities, widely known under the term "Byzantine fault-tolerance". The author introduces these notions in an incremental manner, starting from a clear specification, followed by algorithms which are first described intuitively and then proved correct. The book also presents impossibility results in classic distributed computing models, along with strategies, mainly failure detectors and randomization, that allow us to enrich these models. In this sense, the book constitutes an introduction to the science of distributed computing, with applications in all domains of distributed systems, such as cloud computing and blockchains. Each chapter comes with exercises and bibliographic notes to help the reader approach, understand, and master the fascinating field of fault-tolerant distributed computing.
A one-volume guide to the most essential techniques for designing and building dependable distributed systems Instead of covering a broad range of research works for each dependability strategy, this useful reference focuses on only a selected few (usually the most seminal works, the most practical approaches, or the first publication of each approach), explaining each in depth, usually with a comprehensive set of examples. Each technique is dissected thoroughly enough so that readers who are not familiar with dependable distributed computing can actually grasp the technique after studying the book. Building Dependable Distributed Systems consists of eight chapters. The first introduces the basic concepts and terminology of dependable distributed computing, and also provides an overview of the primary means of achieving dependability. Checkpointing and logging mechanisms, which are the most commonly used means of achieving limited degree of fault tolerance, are described in the second chapter. Works on recovery-oriented computing, focusing on the practical techniques that reduce the fault detection and recovery times for Internet-based applications, are covered in chapter three. Chapter four outlines the replication techniques for data and service fault tolerance. This chapter also pays particular attention to optimistic replication and the CAP theorem. Chapter five explains a few seminal works on group communication systems. Chapter six introduces the distributed consensus problem and covers a number of Paxos family algorithms in depth. The Byzantine generals problem and its latest solutions, including the seminal Practical Byzantine Fault Tolerance (PBFT) algorithm and a number of its derivatives, are introduced in chapter seven. The final chapter details the latest research results surrounding application-aware Byzantine fault tolerance, which represents an important step forward in the practical use of Byzantine fault tolerance techniques.
The present book focuses on the way to cope with the uncertainty created by process failures (crash, omission failures and Byzantine behavior) in synchronous message-passing systems (i.e., systems whose progress is governed by the passage of time). To that end, the book considers fundamental problems that distributed synchronous processes have to solve. These fundamental problems concern agreement among processes (if processes are unable to agree in one way or another in presence of failures, no non-trivial problem can be solved). They are consensus, interactive consistency, k-set agreement and non-blocking atomic commit. Being able to solve these basic problems efficiently with provable guarantees allows applications designers to give a precise meaning to the words "cooperate" and "agree" despite failures, and write distributed synchronous programs with properties that can be stated and proved. Hence, the aim of the book is to present a comprehensive view of agreement problems, algorithms that solve them and associated computability bounds in synchronous message-passing distributed systems. Table of Contents: List of Figures / Synchronous Model, Failure Models, and Agreement Problems / Consensus and Interactive Consistency in the Crash Failure Model / Expedite Decision in the Crash Failure Model / Simultaneous Consensus Despite Crash Failures / From Consensus to k-Set Agreement / Non-Blocking Atomic Commit in Presence of Crash Failures / k-Set Agreement Despite Omission Failures / Consensus Despite Byzantine Failures / Byzantine Consensus in Enriched Models
AN ESSENTIAL GUIDE TO USING BLOCKCHAIN TO PROVIDE FLEXIBILITY, COST-SAVINGS, AND SECURITY TO DATA MANAGEMENT, DATA ANALYSIS, AND INFORMATION SHARING Blockchain for Distributed Systems Security contains a description of the properties that underpin the formal foundations of Blockchain technologies and explores the practical issues for deployment in cloud and Internet of Things (IoT) platforms. The authors—noted experts in the field—present security and privacy issues that must be addressed for Blockchain technologies to be adopted for civilian and military domains. The book covers a range of topics including data provenance in cloud storage, secure IoT models, auditing architecture, and empirical validation of permissioned Blockchain platforms. The book's security and privacy analysis helps with an understanding of the basics of Blockchain and it explores the quantifying impact of the new attack surfaces introduced by Blockchain technologies and platforms. In addition, the book contains relevant and current updates on the topic. This important resource: Provides an overview of Blockchain-based secure data management and storage for cloud and IoT Covers cutting-edge research findings on topics including invariant-based supply chain protection, information sharing framework, and trust worthy information federation Addresses security and privacy concerns in Blockchain in key areas, such as preventing digital currency miners from launching attacks against mining pools, empirical analysis of the attack surface of Blockchain, and more Written for researchers and experts in computer science and engineering, Blockchain for Distributed Systems Security contains the most recent information and academic research to provide an understanding of the application of Blockchain technology.
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.
In modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable and secure distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Failures may range from crashes to adversarial attacks by malicious processes. Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks. 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 topic, covering reliable broadcast, shared memory, consensus, and extensions of consensus. For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming". Its scope has been extended to include security against malicious actions by non-cooperating processes. This important domain has become widely known under the name "Byzantine fault-tolerance".
Timo Warns has developed tractable fault models that, while being non-probabilistic, are accurate for dependent and propagating faults. Using seminal problems such as consensus and constructing coteries, he demonstrates how the new models can be used to design and evaluate effective and efficient means of fault tolerance.
This book aims at being a comprehensive and pedagogical introduction to the concept of self-stabilization, introduced by Edsger Wybe Dijkstra in 1973. Self-stabilization characterizes the ability of a distributed algorithm to converge within finite time to a configuration from which its behavior is correct (i.e., satisfies a given specification), regardless the arbitrary initial configuration of the system. This arbitrary initial configuration may be the result of the occurrence of a finite number of transient faults. Hence, self-stabilization is actually considered as a versatile non-masking fault tolerance approach, since it recovers from the effect of any finite number of such faults in an unified manner. Another major interest of such an automatic recovery method comes from the difficulty of resetting malfunctioning devices in a large-scale (and so, geographically spread) distributed system (the Internet, Pair-to-Pair networks, and Delay Tolerant Networks are examples of such distributed systems). Furthermore, self-stabilization is usually recognized as a lightweight property to achieve fault tolerance as compared to other classical fault tolerance approaches. Indeed, the overhead, both in terms of time and space, of state-of-the-art self-stabilizing algorithms is commonly small. This makes self-stabilization very attractive for distributed systems equipped of processes with low computational and memory capabilities, such as wireless sensor networks. After more than 40 years of existence, self-stabilization is now sufficiently established as an important field of research in theoretical distributed computing to justify its teaching in advanced research-oriented graduate courses. This book is an initiation course, which consists of the formal definition of self-stabilization and its related concepts, followed by a deep review and study of classical (simple) algorithms, commonly used proof schemes and design patterns, as well as premium results issued from the self-stabilizing community. As often happens in the self-stabilizing area, in this book we focus on the proof of correctness and the analytical complexity of the studied distributed self-stabilizing algorithms. Finally, we underline that most of the algorithms studied in this book are actually dedicated to the high-level atomic-state model, which is the most commonly used computational model in the self-stabilizing area. However, in the last chapter, we present general techniques to achieve self-stabilization in the low-level message passing model, as well as example algorithms.