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Headings denoted with an asterisk ( * ) is retrieved from the course syllabus version Autumn 2020
Content and learning outcomes
Course contents
The classical theory of queueing systems:
Discrete and continuous time Markov chains, birth-death processes, and the Poisson process.
Basic terminology of queuing systems, Kendall’s notation and Little’s theorem.
Markovian waiting systems with one or more servers, and systems with infinite as well as finite buffers and finite user populations (M/M/).
Systems with general service distributions (M/G/1): the method of stages, Pollaczek-Khinchin mean-value formula and and systems with priority and interrupted service.
Loss systems according to Erlang, Engset and Bernoulli.
Open and closed queuing networks, Jacksonian networks.
The theory is illustrated by examples from telecommunication and computer communication such as blocking in circuit switched networks, preventive and reactive congestion control, and traffic control for guaranteeing quality of service.
Furthermore, students develop their skills to perform performance analysis of queuing systems and to present the results, using mathematical software and suitable text editors.
Intended learning outcomes
After passing the course, the student should be able to
explain the basic theory of Markov-processes and apply the theory to model queuing systems,
derive and use analytic models of of Markovian queuing systems, queuing networks and also some simpler non-Markovian systems,
explain and use results derived for complex non-Markovian systems,
define queuing models of communication or computer systems, and derive the performance of these systems,
use adequate tools to present scientific work,
in order to be able to carry out mathematical modeling based performance evaluation of communication, computing, or other resource sharing systems.
Learning activities
Lectures: to cover the theory part of the course
Recitations: for problem solving
Home assignments:
- two large home assignments to practice probability theory, and basic queuing theory
- several small home assignments to check the understanding of the theory before attending the recitation
Small project: to solve practical modelling problems and practice the use of mathematical tools.
Preparations before course start
Recommended prerequisites
SF1901 Probability Theory and Statistics, or similar. Basic knowledge in networking is helpful, but not mandatory.
Literature
All reading material is accessible throguh the course web in Canvas. There students can also find suggested books.
Software
Students will have to use Latex as text editor.
Some math software (e.g., Matlab or Matematica) is needed for the project.
Support for students with disabilities
Students at KTH with a permanent disability can get support during studies from Funka:
INL1 - Assignment, 1.5 credits, Grading scale: P, F
TEN1 - Examination, 6.0 credits, Grading scale: A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
The section below is not retrieved from the course syllabus:
Assignment ( INL1 )
Includes two large home assignments, several small home assignments and a small project. Each of these has to be completed to 75% to pass this examination moment.
Examination ( TEN1 )
The format of the final exam is changed in 2022. There is a short written part, followed with an oral part.
Other requirements for final grade
Written examination (TEN1; 5 credits) Written assignment (INL1; 1.5 credits)
Grading criteria/assessment criteria
Assignments: 75% should be completed from each time of assignments.
Exam: 25 out of 50 points is needed for a pass grade.
Opportunity to complete the requirements via supplementary examination
As oral examination is included in the final exam, no students will get Fx.
Opportunity to raise an approved grade via renewed examination
It is allowed to try to raise approved grade in the re-examination period.
Alternatives to missed activities or tasks
Students who did not pass the Assignment moment, but were active throughout the course can receive additional problems to complement.
Reporting of exam results
The results of the Assignments moment are registered within a week after the last deadline.
The results of the final exam, and the final results of the course are registered within three weeks after the final exam.
Ethical approach
All members of a group are responsible for the group's work.
In any assessment, every student shall honestly disclose any help received and sources used.
In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information
Changes of the course before this course offering
Compared to previous course rounds, the course is slightly changed to icrease the diversity of examination and ensure continuous learning.
- additional small home assignemnts from lecture to lecture
- shortened final written exam, which is now in open book format
- additional final oral exam, right after the written exam
Contacts
Communication during course
During the course, please contact via mail:
- the course coordinator with questions related to the course content
- course TA with questions related to recitation problems
- the student administration with administrative matters.
