• Svenska

Course memo Spring 2022

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.

Examination and completion

A, B, C, D, E, FX, F

Examination

• 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.

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.

Written examination (TEN1;  5 credits)
Written assignment (INL1;  1.5 credits)

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

Start date

Missing mandatory information

Course offering

• Spring 2022-60227

English

Offered By

EECS/Computer Science