Introduction to distributed self-stabilizing algorithms /
By: Altisen, Karine [author.].
Contributor(s): Devismes, Stéphane [author.] | Dubois, Swan [author.] | Petit, Franck [author.].
Material type:
BookSeries: Synthesis lectures on distributed computing theory: #15.; Synthesis digital library of engineering and computer science: Publisher: [San Rafael, California] : Morgan & Claypool, [2019]Description: 1 PDF (xvii, 147 pages) : illustrations (some color).Content type: text Media type: electronic Carrier type: online resourceISBN: 9781681735375.Subject(s): Electronic data processing -- Distributed processing | Computer algorithms | distributed computing | distributed algorithms | fault tolerance | transient faults | self-stabilization | convergence | closure | stabilization time | atomic-state model | daemonsGenre/Form: Electronic books.DDC classification: 004/.36 Online resources: Abstract with links to full text | Abstract with links to resource Also available in print.| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
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PK Kelkar Library, IIT Kanpur | Available | EBKE898 |
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Part of: Synthesis digital library of engineering and computer science.
Includes bibliographical references (pages 129-141) and index.
1. Introduction -- 1.1. Parable of the Collatz conjecture -- 1.2. Distributed self-stabilizing systems -- 1.3. Roadmap of this book
2. Preliminaries -- 2.1. Network -- 2.2. Computational model -- 2.3. Self-stabilization -- 2.4. Complexity
3. Coloring under a locally central unfair daemon -- 3.1. The problem -- 3.2. The algorithm -- 3.3. Proof of self-stabilization and silence -- 3.4. Complexity analysis
4. Synchronous unison -- 4.1. The problem -- 4.2. The algorithm -- 4.3. Correctness and time complexity -- 4.4. Related work
5. BFS spanning tree under a distributed unfair daemon -- 5.1. The problem -- 5.2. The algorithm -- 5.3. Proof of self-stabilization and silence -- 5.4. Complexity analysis
6. Dijkstra's token ring -- 6.1. The problem -- 6.2. The algorithm -- 6.3. Study assuming K (n) and a distributed unfair daemon -- 6.4. Study assuming K (n 1) and a locally central unfair daemon
7. Hierarchical collateral composition -- 7.1. Hierarchical collateral composition -- 7.2. A toy example -- 7.3. Hierarchical vs. Nonhierarchical collateral composition
8. Self-stabilization in message passing systems -- 8.1. Message passing for self-stabilizing systems -- 8.2. Related work -- 8.3. A lightweight technique for silent algorithms -- 8.4. Self-stabilization assuming bounded-capacity links -- 8.5. Stabilization time in message passing.
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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 (e.g., the Internet, Pair-to-Pair networks, and Delay Tolerant Networks are examples of such distributed systems). Furthermore, self-stabilization is usually recognized as a lightweightproperty 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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