Universität Wien FIND

052720 VU Advanced Topics in Networks (2019W)

Prüfungsimmanente Lehrveranstaltung

An/Abmeldung

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Montag 07.10. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 14.10. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 21.10. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 04.11. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 11.11. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 18.11. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 25.11. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 02.12. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 09.12. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 16.12. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 13.01. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 20.01. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG
Montag 27.01. 13:15 - 16:30 Seminarraum 6, Währinger Straße 29 1.OG

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The trend toward data-centric applications, related to business, health, or social networking, requires large-scale distributed and network systems which collect and process this data efficiently. Indeed, networked systems (the Internet, datacenter networks, wireless networks, etc.) have become a critical infrastructure of our digital society. The research community currently puts much efforts into the design of solutions to render networked systems more reliable and their performance predictable.

The goal of this course is to make you familiar with some of the state-of-the-art algorithms and cutting-edge techniques and technologies to design networked systems. The course is project-based and hands-on in nature: you will work with existing open-source projects. You will investigate questions such as: Is it possible to reproduce the results researchers presented in their scientific publications? Can you identify weaknesses (in terms of performance or security)? Or even have an idea to improve upon it? At the end of the course, you will write a short paper with your findings. Depending on the results, we may even consider submitting your results to a real conference (the latter is obviously not a requirement and depends on your results, and we will also help you here of course).

At the same time, we in this course are also very much interested in the fundamental aspects of these solutions, and hence, we will teach you some of the algorithms and techniques in the beginning of the course. In particular, we will also teach you how to scientifically evaluate a research idea (e.g., an algorithm): how to set up a simulation, scientific experiment and methodology, so that you can trust in your results? This will not only be useful for your own research, but also to critically examine existing research projects.

You will subsequently choose a topic and project you would like to focus on: we will provide you with a list of possible topics but you are also very welcome to propose one of your own. You will then present your papers/topics in seminar talks, while getting into the details of the implementation.

You can do the project alone or in groups of up to 5 people.

Topics of interest include: low latency networking, design of robust network topologies and protocols, emerging aerial and satellite networks, cryptocurrencies and blockchain, opportunities and formal methods for networked systems, opportunities of machine-learning for networked systems, Industrie 4.0 and fog applications, security of critical infrastructure (e.g., cyberattacks on energy networks), programmable matter etc.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The overall evaluation of student performance will be based on the following components:
- Presentation (20%)
- Paper (60%)
- Oral exam at the end of the teaching period (20%)

No material is permitted during the oral exam.

Mindestanforderungen und Beurteilungsmaßstab

The assessment will be based on the sum of points reached over all of the above elements (% = points). It will follow the scheme:
89 <= points Sehr Gut (1)
75 <= points < 89 Gut (2)
63 <= points < 75 Befriedigend (3)
50 <= points < 63 Genügend (4)
0 <= P < 50 Nicht Genügend (5)

Prüfungsstoff

Topics presented in the slides and in the accompanying literature.

Literatur

Literature will be announced during the course.

Zuordnung im Vorlesungsverzeichnis

Module: AT-NET

Letzte Änderung: Do 05.09.2019 15:27