Guide to Distributed Algorithms Design, Analysis and Implementation Using Python /
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 th...
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| Formato: | Recurso Electrónico livro electrónico |
| Idioma: | inglês |
| Publicado em: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edição: | 1st ed. 2025. |
| Colecção: | Undergraduate Topics in Computer Science,
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| Acesso em linha: | https://doi.org/10.1007/978-3-031-79018-8 |
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| 100 | 1 | |a Erciyes, K. |e author. |0 (orcid)0000-0001-9111-7156 |1 https://orcid.org/0000-0001-9111-7156 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Guide to Distributed Algorithms |h [electronic resource] : |b Design, Analysis and Implementation Using Python / |c by K. Erciyes. |
| 250 | |a 1st ed. 2025. | ||
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| 505 | 0 | |a Part I: Background - 1. Introduction -- 2. Basic Concepts -- 3. Models -- Part II: Fundamental Algorithms -- 4. Time Management -- 5. Distributed Mutual Exclusion -- 6. Distributed Snapshots and Global States -- 7. Coordination -- 8. Fault Tolerance -- 9. Consensus and Agreement -- 10. Multicast Communication and Message Ordering -- 11. Distributed Transactions and Replication -- Part III: Distributed Graph Algorithms - 12. Trees and Traversals -- 13. Weighted Graphs -- 14. Graph Decomposition -- Part IV: Applications -- 15. Mobile Ad hoc Networks -- 16. Wireless Sensor Networks. 17. The Internet and the Internet of Things. | |
| 520 | |a 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 Yaşar University, İzmir, 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. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
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