Lecturer: Professor Frank Fitzek
Assistant: M.Sc. Juan Cabrera
This course introduces the students to the challenges and approaches of the state of the art implementations of network coding. The course is taught not just through lectures, but also with hands-on exercises using the KODO software library.
The initial lectures refresh the knowledge of the students of the theoretical background of network coding, e.g., the min-cut max-flow of a network, inter-flow network coding, and intra-flow Random Linear Network Coding (RLNC). The student is then introduced to the state of the art software library KODO and the advanced implementations of network coding such as systematic, sparse, tunable sparse, sliding window, etc. The course also covers the benefits of network coding in distributed storage applications. By the end of the course, the student will be introduced to advanced applications of network coding, e.g., Coded TCP, MORE, FULCRUM.
The exercises will teach the students how to use sockets in python as well as the python bindings of the KODO software library for implementing unicast and broadcast communication applications.
Language of lecture: English
Optional course, 8th semester
There is a 2 hours written exam. The dates and room will be defined later.
Lectures: Fridays 14:50 – 16:20
Exercises: Thursdays (Every two weeks) 14:50 – 16:20
The slides can be found in this OPAL link.
You need a working Python-Installation with the SciPy-stack.
If you don’t know, what that is or how it is installed, we advise the following steps:
if you don’t know whether you have 32 bit or 64 bit Windows, you can look it up here in
English – https://support.microsoft.com/en-us/kb/827218
or german – https://support.microsoft.com/de-de/kb/827218
In this exercise session, we will work with Kodo. You require a valid Kodo license in order to use the library. Please request a license by filling out the license request form. Kodo is available under a research- and education-friendly license, you can see the details here.
Once you obtain a valid license, please go to the Kodo Python repository here and follow the instructions to build it in your PC.
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Technische Universität Dresden
Faculty of Electrical and Computer Engineering
Institute of Communication Technology
Deutsche Telekom Chair of Communication Networks
01062 Dresden, Germany