Intended learning outcomes
Using a combination of theory and exploration of real data, participants will
gain a deeper understanding of modern computer networks, applications, and
network services. The course complements the basic computer network courses
both in depth and in breadth and will focus on current "hot topics" within the
computer network domain.
Participants successfully completing the course will have experience and be able to:
- explain, in detail, a wide range of technologies used to build data networks;
- explain using concrete examples fundamental network design principles and scalability tradeoffs;
- predict and explain how different networking technologies at the same or different layers interact and affect each other in a large-scale system;
- critically evaluate network technologies with respect to system requirements, based on information from current research and technical documentation;
- design and perform targeted experiments to critically evaluate network technologies, applications, and services;
- apply basic system models and analysis methods to analyze distributed systems and networks;
- plan and conduct an extensive study of an identified problem within a selected area of technology, including integrating knowledge from multiple sources such as current research, technical documentation and experiments from real data sources (in some cases collected by the students themselves);
- generalize and synthesize information from multiple sources (and types of sources) in the computer network area to form original and well-motivated conclusions; and
- based on an in-depth study, present and explain (both written and orally) findings within a selected area of technology, to an audience with similar general knowledge of computer networks.
The precise contents of the course vary from year to year, to keep up with developments in the area, and to focus on currently "hot topics" (e.g., security, privacy, SDN, cloud, VR over network, ML-based traffic classification/detection ...). Recurring topics include: Fundamental properties of computer networks (e.g., Power laws, rich-gets-richer); Scalable systems and designs (e.g., hierarchical vs. flat designs; layered designs); Protocol interactions (e.g., between common protocols such as HTTP, TCP, IP, Ethernet, as well as more application/domain specific protocols), Measurement, modeling and analysis methods using real network data; Important modern computer architectures (e.g., cloud services such as EC2, CDNs, the Internet routing architecture itself, smart grids, and social networks).
Teaching and working methods
The course consists of both theory (lectures, seminars, and paper discussions)
and practical hands-on training and exploration (project). The underlying theme
of the course is to use real data and experiments to understand network
infrastructures and their services. The course has a written final exam. The
project should result in a written report, should be presented in a seminar
during which the students will act as both presenters and opponents (evaluating
and providing each other with feedback, such as to improve the reports and
The course runs over the entire spring semester.
- Written examination (approx. 2.5 credits)
- Project assignment with oral presentation (approx. 3.5 credits)
Active participation in the seminars is compulsory.
Total: 6 credits
All lectures and seminars will be shared with TDTS21 (https://www.ida.liu.se/~TDTS21/). See timedit for scheduling details. However, at a high level, we will have (i) roughly one 2h-long lecture/seminar most weeks (typically Wednesdays), (ii) a mid-term project presentation, (iii) an end-of-term project presentation at the end of the term, and (iv) a final exam at the end of the term.
Doctoral students in computer science/systems/security.
Page responsible: Director of Graduate Studies