Traffic Theory

(German: Nachrichtenverkehrstheorie)

 
Dr.-Ing. Rico Radeke
Lecturer: Dr.-Ing. Rico Radeke
Assistant: Dipl.-Inf. Frank Wilhelm

Overview

This course offers the theoretical base and practical methods for modelling, analysis, and performance investigation of communication systems. The students will learn how to use known formulas for traffic theory problems. The abstraction from reality to model will be done for different practical applications and networks.

Topics covered are:
  • Introduction and Examples
  • Probabilities, Random Distributions, Moments, Properties of distributions
  • Random processes
  • System modelling using traffic theory, terminology, classification, performance measures
  • Little’s law, PASTA, BASTA
  • Theory of Marcov chains (discrete and continous time)t
  • Examples of communication systems to be analyzed with Markov chains
  • Outlook on further tools (matrix analysis, fluid-flow, software tools, Jackson networks, Gordon-Newell, BCMP, Mean value analysis, network calculus (deterministic, stochastic)

Course Schedule

Lectures (L) and Exercises (E), without strict pattern:
Thursday 13:00-14:30 (odd weeks), BAR 213
Friday 11:10-12:40 (weekly), BAR 213

DateRoomTopic
07.04.16BAR 213L1: Introduction to Course, Course Overview, Learning Agreement, Examples, Probabilities, Random Distributions
08.04.16BAR 213E1: Intro to Python, Random Distributions
15.04.16BAR 213L2: Discrete random distributions
21.04.16BAR 213L3: Discrete random distributions (part 2)
22.04.16BAR 213L4: Continous random distributions
29.04.16BAR I/15E2: Random distributions
06.05.16BAR 213L5: Continous random distributions (part 2)
13.05.16BAR 213L6: Moments and random processes
27.05.16BAR 213L7: Markov Processes
02.06.16BAR 213L8: Markov Chains
03.06.16BAR 213E3: Continous random distributions
10.06.16BAR 213E4: Markov Chains
16.06.16BAR 213E5: Ski lift exercise
17.06.16BAR 213L9: Markov chains with continous time
24.06.16BAR 213L10: Equilibrium
30.06.16BAR 213L13: Theory of Markov Chains
01.07.16BAR 213L14: Queues
08.07.16BAR 213L14: Kendall and Little
14.07.16BAR 213L15: Analytic evaluation of systems
E6: Continus Markov Chains
15.07.16BAR 213E7: Systems
10.08.16 14:00BAR I/15Consultation
12.08.16 10:00BAR I/15Exam

Module Number

ET-12 10 05
Module Description in Diplomprüfungsordnung

Material

Material is uploaded to OPAL.

Exam

written, 120min

Exercises

Handson sessions during the lecture and some of the exercises will be solved but the students using Python on their own hardware. So please bring your own hardware, starting with the first exercise on Friday April 8th.  The following preparations would be helpful:

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:

  • install and download “Anaconda” for the right operating system here: https://www.continuum.io/downloads
    Please use Python in version 2.7, and not version 3.4.
  • install and download the programming software “Pycharm” in the free Community Edition from here: PyCharm
  • once this is done we can work with you during the hands-on part of the lecture

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