Course content

Stochastic models of traffic sources, resource demand and user behavior, models of nodes, channels and networks. Transforms. Classical Markovian models. Multidimensional models. Moment methods and imbedded techniques. Systems with priorities. Open and closed queueing networks. Markov modulated processes, fluid flow models. Case studies of broadband networks, mobile networks and Internet using analytical models and simulation. Internet traffic, characterization, measurement methods and statistical problems.

Learning outcome

A. Knowledge:
1) A foundational understanding of terminology and concepts used in describing traffic processes in computer and telecommunication networks / systems, aimed at analysis, measurements and dimensioning.
2) An in-depth understanding of the most fundamental models and methods in classical queueing analysis for computer and telecommunication networks / systems.
3) A basic understanding of traffic analysis models and methods for Internet networks.

B. Skill:
1) To be able to communicate, reason and creatively think about traffic issues in computer and telecommunication networks / systems.
2) To be able to model and evaluate systems quantitatively with respect to traffic performance measures by using the acquired knowledge.

Learning methods and activities

Lectures and voluntary exercises. There is a mandatory semester assignment which requires approval. All teaching material including slides, exercises, and semester assignment is available in English. At a re-sit examination the exam may be changed from written to oral.

Compulsory assignments

• Exercises

Recommended previous knowledge

Course TTM4110 Dependability and Performance with Discrete Event Simulation or similar.

Course materials

To be announced at start of semester.

Credit reductions