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TLT-2736 Traffic Modelling, 3 cr |
Dmitri Moltchanov
Lecture times and places | Target group recommended to | |
Implementation 1 |
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Lectures, exercises, exam.
Completion parts must belong to the same implementation
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This course is devoted to those interested in traffic measurements, statistical analysis, and modeling. The course is divided into two parts. In the first part (3 lectures) the knowledge of probability, statistics and stochastic processes required to understand the content of the course is given. In the second part (7 lectures) we consider the concept of traffic in circuit-switched and packet-switched networks as well as traffic measurements in these networks. Then, we cover well-known traffic models for both circuit-switched and packet-switched networks, show their fundamental properties and limitations and demonstrate their applicability.
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Background information Introduction Reminder of probability Reminder of stochastic processes Reminder of statistics | ||
2. | Traffic modeling Traffic concept and traffic measurements Basic principles of traffic modeling Representation of the arrival processes Renewal traffic models Markovian models Autoregressive models Fluid flow models Long-range dependent, self-similar and non-stationary models Traffic modeling in circuit-switched networks Traffic modeling in packet-switched networks |
The course is evaluated based on: Examination Assignments
Numerical evaluation scale (1-5) will be used on the course
Course | Mandatory/Advisable | Description |
TLT-2106 Basic Course on Networking | Mandatory |
Course | Corresponds course | Description |
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Description | Methods of instruction | Implementation | |
Implementation 1 |