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7.8 MB
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April 20, 2026, 7:43 a.m.
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(Last updated: April 20, 2026, 7:48 a.m.)
| File | Size |
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| Erciyes K. Guide to Distributed Algorithms...Implementation Using Python 2025.pdf | 7.8 MB |
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SOURCE: Erciyes K. Guide to Distributed Algorithms...Implementation Using Python 2025
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MEDIAINFO
Textbook in PDF format 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. Python programming language is selected for the implementation because of its simplicity and for having rich set of libraries that aid to hide low level details such as data manipulations. The mpi4py module of Python is used for distributed algorithm implementations which provides interface for the commonly used Message Passing Interface (MPI) routines. For almost all algorithms, we provide Python code that can be modified and tested for various inputs. All of the Python code can be easily transported to a real distributed environment with the possible modification of send and receive communication procedures of the actual environment, a simple way to achieve this goal is to use the basic socket communications
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