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Distributed Algorithms

Author: Nancy A Lynch
Publisher: San Francisco : Elsevier Science, 1996.
Series: The Morgan Kaufmann Series in Data Management Systems.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers. Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct,  Read more...
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Genre/Form: Electronic books
Databases; Systems Architecture
Additional Physical Format: Print version:
Lynch, Nancy A.
Distributed Algorithms
San Francisco : Elsevier Science,c1996
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Nancy A Lynch
ISBN: 9780080504704 0080504701
OCLC Number: 1027488208
Notes: Description based upon print version of record.
10.7 The Bakery Algorithm
Description: 1 online resource (899 p.)
Contents: Front Cover --
Distributed Algorithms --
Copyright Page --
Contents --
Preface --
Chapter 1. Introduction --
1.1 The Subject Matter --
1.2 Our Viewpoint --
1.3 Overview of Chapters 2-25 --
1.4 Bibliographic Notes --
1.5 Notation --
Part I: Synchronous Network Algorithms --
Chapter 2. Modelling I: Synchronous Network Model --
2.1 Synchronous Network Systems --
2.2 Failures --
2.3 Inputs and Outputs --
2.4 Executions --
2.5 Proof Methods --
2.6 Complexity Measures --
2.7 Randomization --
2.8 Bibliographic Notes --
Chapter 3. Leader Election in a Synchronous Ring --
3.1 The Problem 3.2 Impossibility Result for Identical Processes --
3.3 A Basic Algorithm --
3.4 An Algorithm with O (n log n) Communication Complexity --
3.5 Non-Comparison-Based Algorithms --
3.6 Lower Bound for Comparison-Based Algorithms --
3.7 Lower Bound for Non-Comparison-Based Algorithms --
3.8 Bibliographic Notes --
3.9 Exercises --
Chapter 4. Algorithms in General Synchronous Networks --
4.1 Leader Election in a General Network --
4.2 Breadth-First Search --
4.3 Shortest Paths --
4.4 Minimum Spanning Tree --
4.5 Maximal Independent Set --
4.6 Bibliographic Notes --
4.7 Exercises Chapter 5. Distributed Consensus with Link Failures --
5.1 The Coordinated Attack Problem-Deterministic Version --
5.2 The Coordinated Attack Problem-Randomized Version --
5.3 Bibliographic Notes --
5.4 Exercises --
Chapter 6. Distributed Consensus with Process Failures --
6.1 The Problem --
6.2 Algorithms for Stopping Failures --
6.3 Algorithms for Byzantine Failures --
6.4 Number of Processes for Byzantine Agreement --
6.5 Byzantine Agreement in General Graphs --
6.6 Weak Byzantine Agreement --
6.7 Number of Rounds with Stopping Failures --
6.8 Bibliographic Notes --
6.9 Exercises Chapter 7. More Consensus Problems --
7.1 k-Agreement --
7.2 Approximate Agreement --
7.3 The Commit Problem --
7.4 Bibliographic Notes --
7.5 Exercises --
Part II: Asynchronous Algorithms --
Chapter 8. Modelling II: Asynchronous System Model --
8.1 I/O Automata --
8.2 Operations on Automata --
8.3 Fairness --
8.4 Inputs and Outputs for Problems --
8.5 Properties and Proof Methods --
8.6 Complexity Measures --
8.7 Indistinguishable Executions --
8.8 Randomization --
8.9 Bibliographic Notes --
8.10 Exercises --
Part IIA: Asynchronous Shared Memory Algorithms Chapter 9. Modelling III: Asynchronous Shared Memory Model --
9.1 Shared Memory Systems --
9.2 Environment Model --
9.3 Indistinguishable States --
9.4 Shared Variable Types --
9.5 Complexity Measures --
9.6 Failures --
9.7 Randomization --
9.8 Bibliographic Notes --
9.9 Exercises --
Chapter 10. Mutual Exclusion --
10.1 Asynchronous Shared Memory Model --
10.2 The Problem --
10.3 Dijkstra's Mutual Exclusion Algorithm --
10.4 Stronger Conditions for Mutual Exclusion Algorithms --
10.5 Lockout-Free Mutual Exclusion Algorithms --
10.6 An Algorithm Using Single-Writer Shared Registers
Series Title: The Morgan Kaufmann Series in Data Management Systems.

Abstract:

In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers. Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others. The material is organized according to the system model-first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference. The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms-to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.

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