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Lecturer(s)
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Outrata Jan, doc. Mgr. Ph.D.
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Course content
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The course introduces the latest developments in the area of distributed algorithms. Each topic is supported by recent papers describing applications of the algorithms. The course includes a simulation of a distributed algorithm. 1. Distributed model, wave algorithms 2. Distributed traversal of a network: complexity, correctness 3. Minimum Spanning Tree 4. Snapshot 5. Leader election 6. Anonymous networks 7. Byzantine agreement 8. Routing algorithms Articles: Loop free routing: 1. Loop-Free Internet Routing 2. A Path-Finding Algorithm Boarder Gateway Protocol 1. A Safe Path Vector Protocol 2. Policy Disputes Dual routing 1. Dual routing algorithm 2. Eigrp protocol Clustering 1. Adaptive clustering algorithms Mobile routing 1. Highly Adaptive Algorithm Byzantine Agreement 1. Byzantine failures in Computer Networks Self stabilization 1. Self stabilizing graph algorithms Sensor networks 1. Data gathering 2. Topology control
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Learning activities and teaching methods
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Lecture, Demonstration
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Learning outcomes
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The students become familiar with basic concepts of distributed 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, Written exam
Active participation in class. Completion of assigned homeworks. Passing the oral (or written) 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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Lynch Nancy A. Distributed Algorithms. Morgan Kaufmann.
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Tel Gerard. Introduction to Distributed Algorithms. Cambridge University Press.
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