EP2210 Performance Analysis of Communication Networks 7.5 credits

Prestandaanalys för kommunikationsnätverk

The course focuses on modelling and analyzing communication networks, network protocols and applications, using mathematical tools. It is designed for advanced undergraduates and graduate students.

  • Education cycle

    Second cycle
  • Main field of study

    Information Technology
    Information and Communication Technology
  • Grading scale

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

Course offerings

Autumn 18 for programme students

Information for research students about course offerings

Graduate students should register for EP3210 Advanced Performance Analysis of Communication Networks 9.0 credits, that shares parts of EP2210.

Intended learning outcomes

By the end of the course students will be able to construct tractable models of complex networking problems and attack performance problems with analytical methods or simulation. These abilities are necessary for everyone working on technical fields - to understand the capabilities of specific technologies and the success or failure of new trends.

Course main content

The course consists of 24 hours of lectures, home assignments requiring roughly 20 and project work requiring 30 hours of work by each students.

The course addresses performance issues in current and future Internet architectures:

  • Multi-access communication: CSMA/CD - reservation techniques (token and polling) - packet radio networks (WLANs)
  • Routing in data networks: shortest path routing - optimal routing and topology design
  • Flow control (TCP)
  • Quality of service (QoS) in IP networks: requirements for multimedia transmission - network support: scheduling, shaping, forward error correction
  • Current research topics on network performance


For single course students: 120 credits and documented proficiency in English B or equivalent

Recommended prerequisites

EP2210 Queuing theory and teletraffic systems (or equivalent knowledge);
EP1100 Datacommunication and Computer Networks (or equivalent knowledge)


The course will be based on the book Data Networks by Dimitri Bertsekas and Robert Gallager, Prentice Hall, ISBN 0-13-200916-1 and on selected papers.


  • TEN1 - Examination, 4.5, grading scale: A, B, C, D, E, FX, F
  • ÖVN1 - Exercise, 3.0, grading scale: P, F

Requirements for final grade

Assigned paper (TEN1, 3 credits) Home assignments (OVN, 2 credits).

Offered by



Viktoria Fodor


Viktoria Fodor <vjfodor@kth.se>


Course syllabus valid from: Spring 2019.
Examination information valid from: Spring 2019.