Network Science

PART 1: Basics, concepts and computations of networks

1. Basics of networking en introduction to Network Science

- what is a network?

Representation of a graph, basics of graph theory, overview of the relatively new theory of complex networks, called Network Science. Graph theory is approached from two perspectives: (1) "a topology domain" perspective via graph-related matrices (e.g. the adjacency and Laplacian matrix) and (2) a "spectral domain" perspective via the eigenstructure decomposition (i.e. eigenvectors and eigenvalues) of the graph-related matrix.

- important characterizers of a network (network metrics)

- basic network/graph models

- examples of real-world networks (airline transportation, the web and Internet, social networks, brain networks, etc.) and applications of network science

2. Concepts of networking

- path networks (item follows one path from A to B) and flow networks (current flows over all paths from A to B). Examples of a path network are a telecommunication or road traffic network; example of flow network is an electric resistor network.

- traffic management and scheduling to provide Quality of Service (QoS)

- network robustness (failure, cascading effects,...)

- overlay networking and new aspects of networking such as interdependent networks

PART 2: Applications and examples of networks

(as listed below) will be taught (some of those by a guest lecturer).

Ranging from year to year, a selection among the following will be covered:

1. Electrical networks (smart grids)

2. Networks on Chip (NoC)

3. Optical networks

4. Computer Networks (the Internet)

5. Mobile communication networks

6. Sensor networks

7. Biological networks

8. Social networks