Traffic Engineering: Course Information

Description

Every telecommunication network has to handle unpredictable, bursty traffic while meeting targets for delay, loss and capacity. Traffic engineering supplies the mathematical tools to model that traffic, dimension networks and evaluate their performance. The module starts with a review of random processes, including stationarity, ergodicity, Markov chains and Markov processes. It then develops queuing theory: Poisson processes, Little’s formula, birth–death processes, MMx/x queues and the Erlang formulas, applied to dimensioning loss and delay systems. Students go on to study network traffic models in continuous and discrete time, including self-similar traffic and the Pareto distribution. They also cover fluid flow analysis, which deals with on–off sources, finite and infinite buffers, leaky buckets, equivalent bandwidth and long-range dependent traffic. Practical skills are built through traffic simulation, covering random number generation and discrete-event, time-driven and event-driven methods, and through traffic measurement following ITU-T recommendations. Application examples, including traffic and mobility modelling and the analysis of switches, routers and scheduling algorithms, connect the theory to real networks. On completion, students will be able to model network traffic, apply suitable queuing models to real-world problems and simulate network performance.

The main goal of the course is to equip students to model, analyse and simulate telecommunication network traffic, so they can design and dimension networks that perform reliably under real-world demand.

Intended Audience

BSc students in areas of communication and networking

Course Textbook

• L. Kleinrock, Queueing Systems, Vol. 1: Theory, 1975

• S. M. Ross, Stochastic Processes, 2nd Edition

• S. M. Ross, Introduction to Probability Models, 9th Edition

Lectures

2 hours/week, 14 to 15 weeks

Grading

• Standard university grading applies
  

• The course evaluation consists of

  • Assignments, Project 50%

  • Fnal examination: 50%

Course Learning Outcomes

After finishing the course, the student will be able to

• Describe the different queuing theories related to telecommunication systems and their impact on modeling of telecom networks

• Apply appropriate queuing models to analyze a real world application

• Assess the need for traffic engineering in core networks

• Model network traffic

• Apply the knowledge of traffic theory to simulate real networks

• Analyze the performance of scheduling algorithms used in networks

Working load

4h per Week 14 to 15 weeks

Credits

This is a 3 credit course.

Teaching and learning methodology

The lectures will be mainly based on blackboard and slides.

Prerequisites

Background in introduction to communication, signal and systems, basic probability and statistics

Additional references

• J. M Wozencraft and I. M. Jacobs, Principles of Communication Engineering, 1965

• S. M. Ross, A First Course in Probability, 5th Edition

• F. Gebali, Analysis of Computer and Communication Networks

• J. Shortle, et al, Fundamentals of Queueing Theory, 5th Edition