Traffic Theory

(German: Nachrichtenverkehrstheorie)

 

Lecturer: Dr.-Ing. Rico Radeke
Dr.-Ing. Rico Radeke
Lecturer
rico.radeke@tu-dresden.de

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

Course could be held partially online due to current corona situation.

Lectures (L) and Exercises (E), without strict pattern:

Sommer Semester 2022
Tuesdays 07:30-09:00 (weekly) -> will be changed for SoSe’23
Thursday 13:00-14:30 (even weeks)

Sommer Semester 2023 will be planed, scheduled and published in March 2023 by the faculty
We will give an update here as soon as possible.

DateRoomTopic
Tue, 04.04.22BAR S4L1: Introduction to Course, Course Overview, Learning Agreement, Examples
Thu, 06.04.2022BAR S4L2: Probabilities, Discrete random distributions
Tue, 11.04.2022BAR S4E1: Random distributions
Tue, 18.04.2022BAR S4L3: Continous random distributions
Thu, 20.04.2022BAR S4L4: Moments and stochastic processes
TueBAR S4L5: Markov Chains with Discrete Time (1)
TueBAR S4L5/L6: Markov Chains with Discrete Time (1)/(2)
ThuBAR S4L6: Markov Chains with Discrete Time (2)
TueBAR S4E2: Markov Chains with Discrete Time (1)
TueBAR S4E3: Markov Chains with Discrete Time (2)
ThuBAR S4L7: Markov Chains with Continous Time
TueBAR S4L8: Equilibrium, local and global stability
TueBAR S4L9: Multi-dimensional Markov Chains
ThuBAR S4E4: Markov Chains with Continous Time (1)
TueBAR S4L10: Theory of Markov Chains
TueBAR S4L11: Queues, Kendall, Little
ThuBAR S4L12: Analytic Evaluation of Queueing Systems
TueBAR S4E5: Markov Chains with Continous Time (2)
TueBAR S4E6: Complex Excercises
ThuBAR S4E7: Complex Exercises 2 / Exam Preparation
TueBAR S4L13: Functional Transformations and M_GI_1_inf-System / Wrap Up / Consultation
TueBAR S4Spare Date
July 10-21, 2022t.b.d.Exam

Module Number

ET-12 10 05
Module Description in Diplomprüfungsordnung

Material

Material is uploaded to OPAL (enrollment needed)

Exam

written, 120min

Exercises

Exercises will be on discussion base between students and teaching assistant to focus on unsolved problems.