Guide to Distributed Algorithms: Design, Analysis and Implementation Using Python

· Springer Nature
Ebook
298
Pages
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About this ebook

The study of distributed algorithms provides the needed background in many real-life applications, such as: distributed real-time systems, wireless sensor networks, mobile ad hoc networks and distributed databases.

The main goal of Guide to Distributed Algorithms is to provide a detailed study of the design and analysis methods of distributed algorithms and to supply the implementations of most of the presented algorithms in Python language, which is the unique feature of the book not found in any other contemporary books on distributed computing.

Topics and features:

  • Presents comprehensive design methods for distributed algorithms
  • Provides detailed analysis for the algorithms presented
  • Uses graph templates to demonstrate the working of algorithms
  • Provides working Python code for most of the algorithms presented

This unique textbook/study manual can serve as a comprehensive manual of distributed algorithms for Computer Science and non-CS majors as well as practitioners of distributed algorithms in research projects.

About the author

Dr. Kayhan Erciyes is a full Professor in the Department of Computer Engineering at Yaşar University, İzmir, Türkiye. His other publications include the Springer titles Distributed Real-Time Systems, Guide to Graph Algorithms, Distributed and Sequential Algorithms for Bioinformatics, Discrete Mathematics and Graph Theory.

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