Details

List of Figures xiii<br /><br />List of Tables xxi<br /><br />Acknowledgements xxiii<br /><br />Preface xxv<br /><br />References xxviii<br /><br /><b>1 Introduction to Dependable Distributed Computing 1<br /><br /></b>1.1 Basic Concepts and Terminologies 2<br /><br />1.2 Means to Achieve Dependability 9<br /><br />References 13<br /><br /><b>2 Logging and Checkpointing 15<br /><br /></b>2.1 System Model 16<br /><br />2.2 Checkpoint-Based Protocols 21<br /><br />2.3 Log Based Protocols 34<br /><br />References 54<br /><br /><b>3 Recovery-Oriented Computing 57<br /><br /></b>3.1 System Model 59<br /><br />3.2 Fault Detection and Localization 62<br /><br />3.3 Microreboot 83<br /><br />3.4 Overcoming Operator Errors 87<br /><br />References 93<br /><br /><b>4 Data and Service Replication 97</b><br /><br />4.1 Service Replication 99<br /><br />4.2 Data Replication 105<br /><br />4.3 Optimistic Replication 111<br /><br />4.4 CAP Theorem 131<br /><br />References 138<br /><br /><b>5 Group Communication Systems 141<br /><br /></b>5.1 System Model 143<br /><br />5.2 Sequencer Based Group Communication System 146<br /><b><br /></b>5.3 Sender Based Group Communication System 160<br /><br />5.4 Vector Clock Based Group Communication System 186<br /><br />References 191<br /><br /><b>6 Consensus and the Paxos Algorithms 193<br /><br /></b>6.1 The Consensus Problem <br /><br />6.2 The Paxos Algorithm 196<br /><b><br /></b>6.3 Multi-Paxos 206<br /><br />6.4 Dynamic Paxos 210<br /><b><br /></b>6.5 Fast Paxos 221<br /><br />6.6 Implementations of the Paxos Family Algorithms 229<br /><b><br /></b>References 236<br /><br /><b>7 Byzantine Fault Tolerance 239<br /><br /></b>7.1 The Byzantine Generals Problem 240<br /><br />7.2 Practical Byzantine Fault Tolerance 255<br /><br />7.3 Fast Byzantine Agreement 271<br /><br />7.4 Speculative Byzantine Fault Tolerance 271<br /><br />References 284<br /><b><br /><br /><br /><br /></b><br /><br /><br /><br /><br /><br /><b><br /><br /></b><br /><br /><br /><br /><br />

<p><b>Wenbing Zhao</b> received his PhD in electrical and computer engineering from the University of California, Santa Barbara, in 2002. Currently, he is an Associate Professor in the Department of Electrical and Computer Engineering at Cleveland State University. Dr. Zhao has more than 80 academic publications to his credit, and three of his recent research papers in the area of dependable distributed computing have won best paper awards. Dr. Zhao also has a U.S. patent on consistent time service for fault-tolerant distributed systems.</p>

<p><b>A one-volume guide to the most essential techniques for designing and building dependable distributed systems</b></p> <p>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.</p> <p><i>Building Dependable Distributed Systems</i> 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.</p> <p><b>Readership</b></p> <p>The primary market is networked and distributed computing system designers and developers, software architects, senior software engineers, and technical managers. The book will also prove very useful for upper-level undergraduate and graduate students in computer science and computer engineering interested in dependable computing research.</p>

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