As an assistant professor, I teach university courses. Here, you will find information about the university courses that I teach.

EE2T21 – Data Communications Networking

Data Communications Networking is an introductory course to telecommunication networks. Telecommunication networks include local area networks, the Internet, and telephone networks. This is an obligatory course for second year students that are following the Bachelor Electrical Engineering at the faculty of Electrical Engineering, Mathematics & Computer Science.

Learning Objectives

In this university course, students learn to:

Explain the functionalities with which modern end-to-end communication in data communication networks is achieved.
Explain the architecture and design concepts that underlie the internet and its protocols.
Perform elementary calculations and performance analyses on small networks.
Implement basic mathematical coding and routing algorithms that have inspired error correction methods and routing protocols in networks.

Data Communications Networking, by Piet Van Mieghem

Course material

This course covers Chapters 1 – 7.5 of the book Data Communications Networking, written by professor Piet Van Mieghem. The topics covered are therefore:

Chapter 1. Introduction to data communication networks
Chapter 2. Local Area Networking
Chapter 3. Error control and retransmission protocols
Chapter 4. Architectural principles of the internet
Chapter 5. Flow control protocols in the internet
Chapter 6. Routing algorithms
Chapter 7. Routing protocols

Educational load

The students can earn 2 ECTS by taking this course. This is roughly equivalently to a load of 56 hours. The course is taught in just under 4 weeks. The course is therefore lecture intensive, and a high degree of self-study is expected from the students.

Prerequisites and dependants

No prerequisite university courses are specified for this course. Familiarity is expected with the basic courses taught in the BSc program up to that point. The reason is that this course sits within the second year of our BSc program. The relevant courses include:

EE1M11 – Linear Algebra and Analysis A,
EE1M12 – Linear Algebra and Analysis B, and
EE1M31 – Probability Theory and Statistics.

Follow-up university courses that specify this course as a prerequisite include:

EE4C06 – Networking, and
IN4341 – Performance Analysis.

Sample exam

Here is the exam that students did on July 6th, 2018. This gives you an impression of the contents of the course.

Download

Date	Topic	Location	Presenter
	Chapter 2: Algebraic graph theory
October 3rd, 2018	1. adjacency matrix; 2. admittance matrix, Laplacian; 7-8. line graph; 10-13. permutation matrix, isomorphism and automorphism; 14-15. partitions, quotient matrix; 17-20. walks, paths, diameter, shortest path	HB 09.120	Albert Senen-Cerda
	Chapter 3: Eigenvalues of graphs
October 10th, 2018	21. eigenvalues; 23. Gerschgorin’s theorem; 27-28,31. identities relating graphs properties to eigenvalues; 30. identity relating number of links in a line graph to the number of connected triplets in a graph	HB 09.120	Qiang Liu
October 17th, 2018	33-35. number of walks of length k; 43-44. lower bounding eigenvalues; 50,54. eigenvalue bounds in connected graphs; 64. random walk on a graph, relation between concentration and spectral gap	HB 09.120	Bastian Prasse
Intermezzo
	Chapter 5: Spectra of special types of graphs
January 23rd, 2019	5.1. complete graph; 5.2. small-world graph; 5.3. circuit; 5.4-5.5. path; 5.6. wheel; 5.7. complete bipartite graph;	HB 09.120	Albert Senen-Cerda
	Chapter 6: Density functions of eigenvalues
	121. eigenvalue density function; 123. integral form; 124. trace relation; 128. limiting density function on paths; 130. limiting density function on small world graphs;	HB 09.120	Albert Senen-Cerda
January 30th, 2019	131-133. large sparse regular graphs, McKay’s law; 134-135. random matrices, Wigner’s Semicircle Law; 137. spectrum of the Erdos-Renyi random graph 6.5.2 Marcenko-Pastur’s law	HB 09.120	Jaron Sanders

University Courses