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Before choosing course

Rather than cramming students with the vast volume of baroque queuing theory, this course intends to address more common analytical problems arising in the field of communication networking: (i) how to process simulation and experimental data in a scientific way?; (ii) how to model communication network systems and to analyse their performance metrics?

Though the dizzying variety of theories in the field makes it hard to distinguish the common set of widely applicable theories, the textbook of the course brings a concise set of such theories together in order to answer the above two questions, a part of which has been rarely introduced in the classical books and made accessible only through this textbook. While the interdisciplinary aspects of communication networking are being ever more spotlighted and contemporary networking engineering necessitates all-round engineers trained in theory as well as in practice, careful attention need to be paid to the fact that only a few selected theoretical results lend themselves to engineering problems. This course introduces and elucidates those theoretical concepts for performance evaluation of communication networking, encompassing modern statistics, point process theory, and queuing networks. Among them, Palm Calculus, which was named after Swedish mathematician, Conrad Palm, serves as a theoretical foundation to provide much widened viewpoints on top of queuing theoretical viewpoints.

Last but not least, it is unethical to make a wrong and hasty conclusion only because of the ignorance of suitable analytical techniques.

Course offering missing for current semester as well as for previous and coming semesters
* Retrieved from Course syllabus IK2219 (Autumn 2013–)

Content and learning outcomes

Course contents

This course focuses on broadly applicable methodologies in the field of communication networks, putting special emphasis upon the evaluation of performance therein. A distinctive feature of this course lies in its combination of questions in everyday life and practical problems in communication networks with selected topics in methodologies. In order to help students to gain a better understanding of the methodologies and its applications, the course also contains a set of homework assignments and a project. The textbook can be referred to throughout the academic and industrial careers of students for tackling out various problems in both fields.

§  Content of Lectures

In order to achieve the abovementioned learning outcomes, there are about 11-12 lectures (2 hours) primarily based on the main textbook. The lectures will cover various topics in performance evaluation of communication networks: Summarizing Data (Topic 1), Model Fitting (Topic 2), Tests (Topic 3), Discrete Event Simulation (Topic 4), Palm Calculus (Topic 5), Queuing Theory for Dummies (Topic 6).

§  Review Question Session

Each group of students will present how to solve a few (1-3) selected review questions within a short time (no more than 5 minutes). All review questions and their complete solutions for each topic will be provided by the examiner.

§  Homework Assignments

Introductory Performance Data Summarizations, Random Waypoint Simulation, Queuing Theory from Palm Viewpoint,  Web Server Simulation (Queuing Network)

§  Project Assignment (Group work)

Each group will define a performance evaluation problem in their thesis projects or ongoing research projects and apply methodologies in the course to analyse the problem. If it is impossible for a group to find an appropriate problem, the group will give a talk about a topic or a research paper closely related to performance evaluation in networking.

Intended learning outcomes

This course covers a practical collection of theories and techniques which have been widely applied in the field of communication networking over the past decades. It is no surprise that the subject matter stretches over multiple theories. Upon completion of the course, students are expected to learn how to:

Useful Modern Statistics (Chapters 1-4)

  • Compute confidence interval and prediction interval
  • Fit a suitable model or curve to your measurement data
  • Make assertions on your model in a mathematical manner

Basic Theory for Simulation (Chapter 6)

  • Internalize theoretical framework in order to run simulations correctly

Palm Calculus: the Importance of Viewpoints (Chapter 7)

  • Explain why other queues are always faster when you are shopping

Queuing Theory: Through the Lens of Palm Calculus (Chapter 8)

  • Comprehend useful topics in queuing theory from a fresh angle

Throughout the course, students will learn how to utilize various software packages in conducting simulations and validating analyses.

Course Disposition

Teaching language: English

Literature and preparations

Specific prerequisites

No information inserted

Recommended prerequisites

Required: Basic knowledge in probability (e.g., taking expectation and conditional probability).

Recommended: Basic knowledge in communication networks, e.g., IK1550, IK1551, IK2215, IK2217.

Equipment

No information inserted

Literature

Jean-Yves Le Boudec, “Performance Evaluation of Computer and Communication Systems”, 2010, 1st Edition, EPFL Press. ISBN: 978-2-940222-40-7.


The textbook was published in 2010 by EPFL Press. A free pdf version is available online at http://perfeval.epfl.ch/ by courtesy of EPFL Press.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

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

Examination

  • PRO1 - Project Assignment, 2,5 hp, betygsskala: A, B, C, D, E, FX, F
  • TEN1 - Exam, 2,5 hp, betygsskala: A, B, C, D, E, FX, F
  • UPG1 - Home Assignment, 2,5 hp, betygsskala: 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.

Homework Assignments: 2.5 hp, Project Assignment: 2.5 hp, Written Final Exam: 2.5 hp, Grade scale: A-F 

Other requirements for final grade

The final grade is based on the weighted average of the four examination parts when each part has received a passing grade: review question session (7%), homework assignment (35%), project assignment (28%), and final written exam (30%).

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Profile picture Jeong Woo Cho

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

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web IK2219

Offered by

ICT/Communications Systems

Main field of study

Information and Communication Technology

Education cycle

Second cycle

Add-on studies

No information inserted

Contact

Jeong Woo Cho (jwcho@kth.se)

Supplementary information

Will this course come useful to you?

One of the artistic aspects of performance evaluation lies in that seemingly trivial questions in everyday life are directly related to those encountered in the field. For instance, the following questions will turn out to be not only exquisitely relevant to engineering problems in networking but also crucial for avoiding common repetitious pitfalls in the field:

“Why do we feel that we wait relatively longer than others when shopping in ICA or COOP?” (Palm Calculus)

“Can we validate the ad for a ski resort, ‘capacity doubled, waiting time halved’?” (Queuing Theory)

Some more specific problems you may encounter while conducting research or development are as follows:

“If the data is not normal, what kind of method can be used for computing a confidence interval for an arbitrary performance metric?” (Confidence Interval)

“It is well-known that determining whether truncated data follow power-law or not is an intricate problem. How can we test and quantify the goodness of a certain distribution to the data?” (Tests)

“It takes months to estimate by simulation the probability of a very rare event, e.g., a bit error rate of 10-10. Is there any other way around this?” (Discrete Event Simulation)

Answers to all the aforementioned questions and their implications will be taught in the course.