Traffic Theory

(German: Nachrichtenverkehrstheorie)

 

Lecturer: Dr.-Ing. Rico Radeke
Lecturer

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:
Tuesdays 07:30-09:00 (weekly)
Thursday 13:00-14:30 (even weeks)
Alternative: Friday 13:00-14:30 (odd weeks)

DateRoomTopic
Tue, 05.04.2022 07:30ZEU 148L1: Introduction to Course, Course Overview, Learning Agreement, Examples
Thu, 07.04.2022 13:00BAR S4L2: Probabilities, Discrete random distributions
Tue, 19.04.2022 07:30BAR S4L3: Continous random distributions
Thu, 21.04.2022 13:00BAR S4L4: Moments and stochastic processes
Tue, 26.04.2022 07:30BAR S4E1: Random distributions
Fri, 29.04.2022 13:00BAR S4L5: Markov Chains with Discrete Time (1)
Tue, 03.05.2022 07:30BAR S4L5/L6: Markov Chains with Discrete Time (1)/(2)
Thu, 05.05.2022 13:00BAR S4L6: Markov Chains with Discrete Time (2)
Tue, 17.05.2022 07:30BAR S4E2: Markov Chains with Discrete Time (1)
Thu, 19.05.2022 13:00BAR S4E3: Markov Chains with Discrete Time (2)
Tue, 24.05.2022 07:30BAR S4L7: Markov Chains with Continous Time
Fri, 27.05.2022 13:00 (??)BAR S4--- no lecture ---
Tue, 31.05.2022 07:30BAR S4L8: Equilibrium, local and global stability
Thu, 02.06.2022 13:00 (??)BAR S4L9: Multi-dimensional Markov Chains
Tue, 14.06.2022 07:30BAR S4--- no lecture ---
Thu, 16.06.2022 13:00BAR S4E4: Markov Chains with Continous Time (1)
Tue, 21.06.2022 07:30BAR S4L10: Theory of Markov Chains
Fri, 24.06.2022 13:00BAR S4L11: Queues, Kendall, Little
Tue, 28.06.2022 07:30BAR S4L12: Analytic Evaluation of Queueing Systems
Thu, 30.06.2022 13:00BAR S4E5: Markov Chains with Continous Time (2)
Tue, 05.07.2022 07:30BAR S4E6: Complex Excercises
Fri, 08.07.2022 13:00BAR S4E7: Complex Exercises 2 / Exam Preparation
Tue, 12.07.2022 07:30BAR S4L13: Functional Transformations and M_GI_1_inf-System / Wrap Up / Consultation
Thu, 14.07.2022 13:00BAR S4--- no lecture ---
Fri, 15.07.2022 13:00ZEU 146Exam

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.