Distributed Algorithms

Distributed Algorithms
Author :
Publisher : Elsevier
Total Pages : 899
Release :
ISBN-10 : 9780080504704
ISBN-13 : 0080504701
Rating : 4/5 (04 Downloads)

Book Synopsis Distributed Algorithms by : Nancy A. Lynch

Download or read book Distributed Algorithms written by Nancy A. Lynch and published by Elsevier. This book was released on 1996-04-16 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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