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Introduction to Distributed Self-Stabilizing Algorithms (Synthesis Lectures on Distributed Computing Theory) - Softcover

 
9781681735368: Introduction to Distributed Self-Stabilizing Algorithms (Synthesis Lectures on Distributed Computing Theory)

Synopsis

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 a 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.

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About the Author

Karine Altisen is an associate professor at Grenoble-INP/Ensimag (France). She has been a member of the VERIMAG Laboratory since 1998 and obtained a Ph.D. in 2001. Her current research area combines formal methods and distributed computing. She is interested in theoretical and algorithmic aspects of fault-tolerant distributed systems, including their certification.

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  • PublisherMorgan & Claypool Publishers
  • Publication date2019
  • ISBN 10 1681735369
  • ISBN 13 9781681735368
  • BindingPaperback
  • LanguageEnglish
  • Number of pages166

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9781681735382: Introduction to Distributed Self-stabilizing Algorithms (Synthesis Lectures on Distributed Computing Theory)

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ISBN 10:  1681735385 ISBN 13:  9781681735382
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Published by Morgan & Claypool Publishers, 2019
ISBN 10: 1681735369 ISBN 13: 9781681735368
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