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Lecturer(s)
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Outrata Jan, doc. Mgr. Ph.D.
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Masopust Tomáš, prof. RNDr. Ph.D., DSc.
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Course content
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The course covers selected distributed algorithms for advanced problems, including: - Mutual exclusion, deadlock detection, and termination detection. - Garbage collection: reference counting and tracing. - Routing algorithms. - Leader election. - Anonymous and synchronous networks. - Byzantine agreement. - Stabilizing algorithms.
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Learning activities and teaching methods
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Dialogic Lecture (Discussion, Dialog, Brainstorming), Work with Text (with Book, Textbook)
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Learning outcomes
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The students become familiar with basic concepts of distributed algorithms. The students will expand their knowledge of basic problems of distributed systems and their solution algorithms and become familiar with selected advanced aspects and algorithms.
1. Knowledge Describe and understand comprehensively principles and methods of distributed algorithms.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral exam
Completing the assignments. Passing the exam.
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Recommended literature
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Attiya Hagit, Welch Jennifer. (2004). Distributed Computing: Fundamentals, Simulations, and Advanced Topics, 2nd Edition.
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Ben-Ari M. (2006). Principles of concurrent and distributed programming. Addison.
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Ghos, S. (2007). Distributed systems. Chapman & Hall/CRC.
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Lynch Nancy A. Distributed Algorithms. Morgan Kaufmann.
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Tel Gerard. Introduction to Distributed Algorithms.
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van Steen. M, Tanenbaum A. (2017). Distributed Systems.
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