The new edition of a guide to Distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models.
Distributed Algorithms can be used in courses for upper-level undergraduates or graduate students in computer science, or as a reference for researchers in the field..
Solutions and slides are available for instructors.
An appendix offers pseudocode descriptions of many algorithms.
Sections have been added that cover such subjects as rollback recovery, fault-tolerant termination detection, and consensus for shared memory.
A new chapter on security discusses two exciting new topics: blockchains and quantum cryptography.
A new chapter on Distributed transaction offers up-to-date treatment of database transactions and the important evolving area of transactional memory.
This second edition has been substantially revised.
The algorithms presented in the book are for the most part classics, selected because they shed light on the algorithmic design of Distributed systems or on key issues in Distributed computing and concurrent programming.
Proof sketches, arguing the correctness of an algorithm or explaining the idea behind fundamental results, are also included.
The examples and exercises allow readers to understand algorithms intuitively and from different perspectives.
Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises.
This Approach allows the student to learn a large number of algorithms within a relatively short span of time.
It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic.
This book offers students and researchers a guide to Distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models.
The new edition of a guide to Distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models
