Course Syllabus for

Queuing Theory

EIT046F, 7.5 credits

Valid from: Autumn 2013
Decided by: FN1/Björn Regnell
Date of establishment: 2013-11-08

General Information

Division: Electrical and Information Technology
Course type: Third-cycle course
Teaching language: English


Modern multi-service communication systems are designed to support a large variety of flows. This is in contrast with traditional telecommunication systems where the dominant service was telephony. However, distributed server systems exhibit many similarities with traditional telecommunication systems from a stochastic performance point of view. It is necessary to understand the similarities and differences between these systems and their performance models in order to effectively conduct research in the areas of communication networks and distributed systems. Specifically, it is of utmost importance to be able to evaluate algorithm and component design when placed in their operational systems context in order to be able to compare design solutions and to be able to derive theoretical performance bounds. This course extends the material coverage from foundational queuing theory courses and studies in-depth, the effects of individual and combinations of different traffic regimes. The course also covers modeling of highly complex systems which enables the researcher to draw generalised conclusions about queuing modeling results. Students who successfully complete the course will be equipped with a deep understanding of the use of queuing theory to investigate and design distributed stochastic systems.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must

Course Contents

The course covers queuing theory with applications in general distributed systems. The material focusses on the fundamental principles for the derivation of queuing models and their application in performance modeling. Strong emphasis is placed on modeling using Markov chains and the development of complex systems models from scratch. The course further covers different system models from distributed systems and networks and compares and contrasts them. Finally, the course covers the effects of heavy tailed distributions in both arrival rates and service rates.

Course Literature

Kleinrock, L.: Queueing Systems. Wiley.

Instruction Details

Types of instruction: Lectures, project, self-study literature review

Examination Details

Examination formats: Oral exam, written assignments, seminars given by participants
Grading scale: Failed, pass

Admission Details

Further Information

Course coordinator: Björn Landfeldt,

Course Occasion Information

Contact and Other Information

Course coordinators:

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