Guide to Distributed Algorithms: Design, Analysis and Implementation Using Python
| AUTHOR | Erciyes, K.; Erciyes, Kayhan |
| PUBLISHER | Springer (04/23/2025) |
| PRODUCT TYPE | Paperback (Paperback) |
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.
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.
Dr. K. Erciyes is a professor of Computer Engineering at Ya?ar University, ?zmir, Turkiye. His other publications include the Springer titles Distributed Graph Algorithms for Computer Networks, Distributed and Sequential Algorithms for Bioinformatics, Guide to Graph Algorithms, Distributed Real-Time Systems, Discrete Mathematics and Graph Theory and Algebraic Graph Algorithms.
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.