Distributed Algorithms (The Morgan Kaufmann Series in Data...

Features

• Cover Type: Hard Cover with 904 pages
• Published by: Morgan Kaufmann
• Edition: 1st Edition April 1997
• Written in: English
• ISBN 10 Number: 1558603484
• ISBN 13 Number: 978-1558603486
• Book Dimensions: 9.3 x 7.6 x 1.7 inches
• Weighs: 3.8 pounds

Product Review
Shows students, programmers, system designers and researchers how to design, implement, and analyze distributed algorithms. Familiarizes readers with the most important problems, algorithms, and impossibility results in the area.

Provides the basic mathematical tools for designing new algorithms and proving new impossibility results. Teaches 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.

Features:
* 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 analyzed according to precisely-defined complexity measures.
* The problems covered include resource allocation, communication, consensus among distributed processors, data consistency, deadlock detection, leader election, global snapshots, and many others.


The material is organized according to the system model -- first, according to the timing model, and then, by the interprocess communication mechanism. The material on system models is isolated into separate chapters for easy reference. -- Book Description

This is the finest texbook it has been my pleasure to review, and I strongly recommend it to both the specialist and the merely interested reader. The real contribution comes from the presentation of so many algorithms in a common and usable style. It does for distributed algorithms what Knuth Volume I did for sequential ones. -- Julian Padget (Mathematical Reviews, January 1997)

Product Description


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.

Reader Reviews
Professor's Nancy Lynch's "Distributed Algorithms" is a definite reference for theoretical treatments of many hard problems in distributed computing. It is a textbook, but written in such a clear style that makes it almost a pleasure read. Rarely have I seen something like that! The book has a right proportion of theoretical proofs, practical applications, philosophical appreciation of the problems, research questions, examples and study points. "Distributed Algorithms" has 3 main parts - synchronous, asynchronous and partially synchronous network algorisms. Each part describes consensus resolution, mutual exclusion, resource allocation, leader election, termination detection and failure detection as main problems in distributed computing theory. Lynch has done a masterful job of leading us from simple to complex, from theoretically solvable to practically intractable problems. For a practitioner of computer science, who is not necessarily involved in fundamental research, this book gives a clear appreciation of problems of 2PC, resource management, failure profiles in faulty and noisy networks, optimization and fault management in distributed networks. All those things are foundations of databases, network computing and enterprise scalability. It also helped me greatly in estimating the best and worst case boundaries in certain practical distributed system optimization problems.