Guide to Distributed Algorithms
Design, Analysis and Implementation Using Python
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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 desig...
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 algorithmsProvides detailed analysis for the algorithms presentedUses graph templates to demonstrate the working of algorithmsProvides 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 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 algorithmsProvides detailed analysis for the algorithms presentedUses graph templates to demonstrate the working of algorithmsProvides 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.
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