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Books > Computers & Technology > Networking & Cloud Computing > Data in the Enterprise > Client-Server Systems > B00HAZZN7I
  1. Distributed Algorithms: An Intuitive Approach (MIT Press)
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  2. Distributed Algorithms: An Intuitive Approach (MIT Press)

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This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises. The examples and exercises allow readers to understand algorithms intuitively and from different perspectives. Proof sketches, arguing the correctness of an algorithm or explaining the idea behind fundamental results, are also included. An appendix offers pseudocode descriptions of many algorithms.Distributed algorithms are performed by a collection of computers that send messages to each other or by multiple software threads that use the same shared memory. 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.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.

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Wan Fokkink
Kindle Edition
Kindle eBook
The MIT Press
The MIT Press
The MIT Press
The MIT Press
Most Helpful Customer Reviews

Review based on the first 7 chapters.

The book skips proofs and just explains why the algorithms work, often with examples and pictures. This I like very much.

Caveat: Many of the algorithms given in the book assume a model of distributed computation where messages are not lost and nodes (processes) do not die. In other words, many of these algorithms are not applicable in modern Google-style shared-nothing distributed computing, where you have 1000s of components in a datacenter, and at any one time, a number of them will be failing or unreachable. These are algorithms for multiple processes (processors) in a single computer, where message passing is reliable and processes don't randomly die. That's fine, but I wish the book's title or description would have been clear about this.

Since most of my past readings were in algorithms that work in the case of failures and message loss (like Paxos) I did find the book educational.
Very disappointed with this book, bought with the high hopes after going through couple of reviews here but the book turned out to be a very boring one. Seemed to contain nothing but a collection of short (published) papers for e.g. Deadlock detection, Termination detection, Leader election and etc. I would have benefited if the authors had spent more time explaining each of the algorithms in detail rather than presenting short description of how they work with minimal or no examples.
Few texts in Distributed Algorithms strike a balance between rigor and accessibility; this one does. Recommended for the practitioner in distributed systems ; a careful reading will supply the theoretical foundation for thinking about problems in distributed computing. Note that there is very little code here , but a great deal of thinking is required to get something from this text. (Sorry for brevity ... typed on my iphone)
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