Amazon cover image
Image from Amazon.com

Distributed algorithms : an intuitive approach / Wan Fokkink

By: Material type: TextTextPublication details: Cambridge, Massachusetts : The MIT Press, c2013Description: x, 231 pages : illustrations ; 23 cmISBN:
  • 9780262026772
Subject(s): LOC classification:
  • QA 76.58 .F65 2013
Contents:
I Message Passing; 2 Preliminaries; 3 Snapshots; 4 Waves; 5 Deadlock Detection; 6 Termination Detection; 7 Garbage Collection; 8 Routing; 9 Election; 10 Anonymous Networks; 11 Synchronous Networks; 12 Crash Failures; 13 Byzantine Failures; 14 Mutual Exclusion; II Shared Memory; 15 Preliminaries; 16 Mutual Exclusion II; 17 Barriers; 18 Self-Stabilization; 19 Online Scheduling; Pseudocode Descriptions; References; Index.
Summary: "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 be used in courses for upper-level undergraduates or graduate students in computer science, or as a reference for researchers in the field."
Item type: Books
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Home library Collection Call number Copy number Status Date due Barcode
Books Books National University - Manila LRC - Main General Circulation Machine Learning GC QA 76.58 .F65 2013 (Browse shelf(Opens below)) c.1 Available NULIB000013744
Browsing LRC - Main shelves, Shelving location: General Circulation, Collection: Machine Learning Close shelf browser (Hides shelf browser)
GC QA 76.9.S88 .K46 2011 c.1 Systems analysis and design / GC QA 76.9.S88 .K46 2011 c.5 Systems analysis and design / GC QA 76.58 .B37 2016 Parallel and distributed computing : architectures and algorithms / GC QA 76.58 .F65 2013 Distributed algorithms : an intuitive approach / GC QA 76.58 .R39 2014 Fundamentals of parallel computing / GC QA 76.73 .C46 2021 Deep learning with python / GC QA 76.73 .S35 2018 c.2 Java a beginner's guide /

Includes bibliographical references and index.

I Message Passing; 2 Preliminaries; 3 Snapshots; 4 Waves; 5 Deadlock Detection; 6 Termination Detection; 7 Garbage Collection; 8 Routing; 9 Election; 10 Anonymous Networks; 11 Synchronous Networks; 12 Crash Failures; 13 Byzantine Failures; 14 Mutual Exclusion; II Shared Memory; 15 Preliminaries; 16 Mutual Exclusion II; 17 Barriers; 18 Self-Stabilization; 19 Online Scheduling; Pseudocode Descriptions; References; Index.

"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 be used in courses for upper-level undergraduates or graduate students in computer science, or as a reference for researchers in the field."

There are no comments on this title.

to post a comment.