Advanced Networking
People
Course director
Assistant
Description
This course covers advanced topics in computer networks, with a blendof theoretical and practical topics. On the theoretical side, the syllabus will cover mathematical foundations of networking, including discussions of queuing theory, simulation, and traffic engineering and optimization. On the practical side, the syllabus will cover concepts and designs related to modern network architectures and technologies (e.g., data-center networks, software-defined networks), as well as protocols at various levels (e.g., HTTP/2, QUIC, DCTCP, IPSec, MPLS). Students will gain hands-on experience by using network applications, simulators, and emulators, and by developing solutions for a series of exercises more or less related to the topics discussed in class.
Objectives
This course has two main objectives. First, we want to acquire an in-depth understanding of basic notions in networking, such as queuing, routing, and congestion control. Second, we want to present advanced concepts and protocols.
Teaching mode
In presence
Learning methods
The course builds on traditional lectures. Students will gain hands-on experience with the topics discussed in class through a series of exercises using simulation, emulation (Mininet), as well as tools for network design.
Examination information
Homework assignments and/or projects, all consisting of concrete problems, including network-design and optimization, simulation, and protocol implementations. Seminar presentations of important and relatively recent papers in Computer Networking.
Education
- Master of Science in Artificial Intelligence, Lecture, Elective, 1st year
- Master of Science in Artificial Intelligence, Lecture, Elective, 2nd year
- Master of Science in Computational Science, Lecture, Elective, 1st year
- Master of Science in Computational Science, Lecture, Elective, 2nd year
- Master of Science in Informatics, Lecture, Computer Systems, Elective, 1st year
- Master of Science in Informatics, Lecture, Computer Systems, Elective, 2nd year
- Master of Science in Informatics, Lecture, Information Systems, Elective, 1st year
- Master of Science in Software & Data Engineering, Lecture, Elective, 1st year
- PhD programme of the Faculty of Informatics, Lecture, Elective, 1st year (4.0 ECTS)