Course: Parallel and Distributed Algorithms

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Course title Parallel and Distributed Algorithms
Course code KMI/PGDA
Organizational form of instruction Lecture
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 5
Language of instruction Czech, English
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Outrata Jan, doc. Mgr. Ph.D.
Course content
The course repeats the basics of parallel programming, problems in distributed systems and their solution algorithms and introduces selected advanced problems and distributed algorithms. The course extends the introductory parts of the master's studies. 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

Learning activities and teaching methods
Dialogic Lecture (Discussion, Dialog, Brainstorming), Work with Text (with Book, Textbook)
Learning outcomes
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.
Prerequisites
unspecified

Assessment methods and criteria
Oral exam

Completing the assignments. Passing the exam.
Recommended literature
  • Attiya Hagit, Welch Jennifer. (2004). Distributed Computing: Fundamentals, Simulations, and Advanced Topics, 2nd Edition.
  • Ben-Ari M. (2006). Principles of concurrent and distributed programming. Addison-Wesley.
  • Ghos, S. (2007). Distributed systems. Chapman & Hall/CRC.
  • Lynch Nancy A. Distributed Algorithms. Morgan Kaufmann.
  • Tel Gerard. Introduction to Distributed Algorithms. Cambridge University Press.
  • van Steen. M, Tanenbaum A. (2017). Distributed Systems. CreateSpace Independent Publishing Platform.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester