Courses

Communication Networks (Spring 2022)

Prof. Laurent Vanbever

The students will understand the fundamental concepts of communication networks, with a focus on computer networking. They will learn to identify relevant mechanisms that are used in networks, and will see a reasonable set of examples implementing such mechanisms, both as seen from an abstract perspective and with hands-on, practical experience.

Past iterations: 2021 | 2020 | 2019 | 2018 | 2017 | 2016

Advanced Topics in Communication Networks (Autumn 2022)

Prof. Laurent Vanbever, Dr. Romain Jacob

This course covers advanced topics and technologies in computer networks, both theoretically and practically. In the Fall 2022, the course will cover advanced topics in Internet routing and forwarding. The goal for this course is to provide students with a deeper understanding of existing and upcoming Internet routing and forwarding technologies used in large-scale computer networks such as Internet Service Providers (e.g., Swisscom or Deutsche Telekom), Content Delivery Networks (e.g., Netflix) and Data Centers (e.g., Google). Besides covering the fundamentals, the course will be “hands-on” and will enable students to play with the technologies in realistic network environments, and even implement some of them on their own during labs and a final group project.

Past iterations: 2021 | 2020 | 2019 | 2018

Seminar in Communication Networks (Spring 2022)

Prof. Laurent Vanbever, Dr. Romain Jacob

In this seminar participating students review, present, and discuss (mostly recent) research papers in the area of computer networks. 

Past iterations: 2021 | 2020 | 2019

Discrete Event Systems (Autumn 2022)

Prof. Lana Josipovic, Prof. Laurent Vanbever, Prof. Roger Wattenhofer

In this lecture we give an introduction to discrete event systems. We start out the course by studying popular models of discrete event systems, such as automata and Petri nets. In the second part of the course we analyze discrete event systems. We first examine discrete event systems from an average-case perspective: we model discrete events as stochastic processes, and then apply Markov chains and queuing theory for an understanding of the typical behavior of a system. In the last part of the course we analyze discrete event systems from a worst-case perspective using the theory of online algorithms and adversarial queuing.

Past iterations: 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015