Network Application Diagnostics

Course guarantor:

Radek Mařík

Lecturer:

Radek Mařík

Tutor:

Vojtěch Drahý, Radek Mařík, Tomáš Zikmund

Supervisor:

Department of Telecommunications Engineering

Synopsis:

The first part of the course covers the modeling of complex network structures, the identification of their characteristics, the recognition of static and dynamic structural patterns, the detection of potential anomalies, and the application of deep learning and graph neural networks. The use of these methods is demonstrated through examples of problems encountered in network applications. The practical sessions focus on acquiring hands-on skills by solving real-world problems.

Requirements:

- Knowledge of linear algebra and graph theory.

- Knowledge of network application and protocol fundamentals.

- Seminar tasks might be implemented in any programming language, Python is recommended.

Syllabus of lectures:

1. Introduction to complex networks

2. Graph theory

3. Basic network properties and random graph models

4. Characterization of network nodes

5. Network structure

6. Community detection

7. Network evolution and dynamic network processes

8. Introduction to machine learning

9. Semantic information & large language models

10. Graph neural networks

11. Automata testing and characterization set

12. Automata detection sequences

13. Automata learning

14. Consultation

Syllabus of tutorials:

1. Introduction and organization of exercises.

2. Graph theory and path analysis.

3. Random graph models.

4. Characterization of network nodes.

5. Network structure.

6. Community detection.

7. Simulation of dynamic networks.

8. Introduction to machine learning.

9. Semantic information.

10. Graph neural networks.

11. Automata testing.

12. Automata detection sequences.

13. Automata learning.

14. Semester test and pre-exam consultation.

Study Objective:

The course introduces the mathematical, theoretical, and practical foundations necessary to master the diagnostics of systems that can be modeled as complex network structures.

Study materials:

- Networks: An Introduction, M. E. J. Newman, Oxford University Press (2010)

- Networks, Crowds, and Markets: Reasoning about a Highly Connected World, Easley, D., Kleinberg, J.; Cambridge University Press, 2010

Note:

Further information:

https://cw.fel.cvut.cz/wiki/courses/b2m32dsaa

Time-table for winter semester 2025/2026:

	06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue
Wed
Thu	roomT2:B3-700 Mařík R. 16:15–17:45 (lecture parallel1) Dejvice roomT2:B3-700 18:00–19:30 (lecture parallel1 parallel nr.101) Dejvice
Fri

Time-table for summer semester 2025/2026:

Time-table is not available yet

The course is a part of the following study plans:

• Electronics and Communications - Technology of the Internet of Things (compulsory elective course)
• Electronics and Communications - Communication Networks and Internet (compulsory elective course)
• Electronics and Communications - Communication Networks and Internet (compulsory elective course)