The course on Network Science aims to provide a general and basic introduction to the art of “networking”, that tries to unravel
the operation and behavior of networks, both man-made (infrastructures such as the Internet, power grids and transportation networks) as well as
networks appearing in nature (such as the human brain, biological networks and social human interactions).
The course on Network Science introduces the concepts of Network Science, the theory of networks that basically studies the interplay
between, on the one hand, the processes - also called functions or services - on the network and, on the other hand,
the underlying topology, graph or structure, that can also change over time as an evolving organism.
Network Science combines many disciplines such as graph theory, probability theory,
stochastic processes, physical laws, control theory, algorithms and aspects of social sciences.
After this course, students are expected to represent/abstract real-world infrastructural
network (e.g. a communication system) as a complex network, understand the basic methods
to analyze properties of networks and dynamic processes on networks.
Students will also understand why processes on networks and design of networks are so complex.
Finally, students may appreciate the fascinatingly rich structure and behavior of networks
and may realize that much in the theory of networks still lies open to be discovered.
Course Outline
- PART 1: Network topology or graph
- Basics of networking and introduction to Network Science
- Graph theory: what is a network? Representation of a graph, overview of the relatively new theory of complex networks,
called Network Science.
- Graph metrics: important characterizers of a network (network metrics)
- Graph models
- Examples of real-world networks (airline transportation, the web and Internet, social networks, brain networks, etc.) and applications of network science
- PART 2: Network function or process and service
- Electrical networks: the power of the Laplacian and the effective resistance matrix
- Communication networks: principles of traffic management and scheduling
- multi-layered and interdependent networks
- network robustness (failure, cascading effects,...)
- PART 3: Applications and examples of networks
Some classes will be taught by a guest lecturer. Ranging from year to year, a selection among the following will be covered:
- Electrical networks (smart grids)
- Networks on Chip (NoC)
- Optical networks
- Computer Networks (the Internet)
- Mobile communication networks
- Sensor networks
- Biological networks
- Social networks
- Transportation networks
Course announcements
- TUDelft code: EE4C06
- 5 EC
- The course material consists of the slides posted on Brightspace after each class. The slides will contain references to the literature providing an extra depth.
In particular, references to Graph Spectra for Complex Networks, Second edition, 2023 will be added in the slides.
- The examination is an open book examination.
- Due to the large number of interested students (> 250 over the last years), the examination consists of 20 multiple choice questions in Brightspace on a computer.
- There are precisely two examination possibilities per year.
- All other announcements are mentioned on Brightspace.
Last modified: 1-10-2025