Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.


After the course the students are able to measure and analyze basic properties of network traffic and draw conclusions on the results. They obtain skills to apply and evaluate statistical methods in processing, analyzing and presenting the measurement data. Students gain understanding of the technical and legal issues related to network measurements and become familiar with the related methods and software tools.

Credits: 5

Schedule: 09.09.2020 - 30.11.2020

Teacher in charge (valid 01.08.2020-31.07.2022): Esa Hyytiä, Markus Peuhkuri

Teacher in charge (applies in this implementation): Esa Hyytiä, Markus Peuhkuri

Contact information for the course (valid 21.08.2020-21.12.2112):

Markus Peuhkuri <>

CEFR level (applies in this implementation):

Language of instruction and studies (valid 01.08.2020-31.07.2022):

Teaching language: English

Languages of study attainment: English


  • Valid 01.08.2020-31.07.2022:

    This course introduces different ways of measuring Internet traffic and provides an overview on tools that can be utilized to analyze the results. Course topics include packet, flow and routing related measurements and their analysis. Also related technical and legal issues are covered. Exercises include measurement data processing and analysis using statistical/mathematical software. In the assignment, data traffic measurements are performed, analysed and reported.

  • Applies in this implementation:

    This course will provide you practical skills to do communication
    network measurements. You are introduced with basic tools that allow
    you to perform measurements and collect results. Majority of tools
    covered are Linux command line tools that are de-facto standards in
    network engineering and scientific community.

    Collected measurement data is then processed, analysed and
    presented by applying statistical methods. You will learn
    applicability of the methods for each situatuation. Recommended
    environments include python and R.

    Network measurements can include personally identifiable
    information (PII). Legal framework and regulation that dicatetes how
    data can be collected, processed and stored are discussed.

Assessment Methods and Criteria
  • Valid 01.08.2020-31.07.2022:

    Compulsory: Examination, assignment(s), exercises.

  • Applies in this implementation:

    There are 5 mandatory weekly assignment that provide maximum 30
    points. These weekly exercises provide skills needed for the final

    The final assignment contributes 70 points for total 100 points.

    Each assignment report must be based on individually collected
    measurement data and the report, including figures, must be
    individual work. Students are, however, encouraged to co-operate and
    help others.

  • Valid 01.08.2020-31.07.2022:

    Contact hrs 37 h
    Independent learning (incl. assignment): 96 hours

  • Applies in this implementation:

    • Lectures 24

    • Excersises 12

    • Self-study on
      material: 24 hours

    • Weekly
      excersises: 36 hours

    • Final assignment:
      36 hours


Study Material
  • Applies in this implementation:

    • Lecture notes
      by Markus Peuhkuri (65 pages)

    • Lecture slides
      for other lectures

    • Supporting
      material for assignments

Substitutes for Courses
  • Valid 01.08.2020-31.07.2022:


  • Valid 01.08.2020-31.07.2022:

    Basic probability theory and statistics (e.g., MS-A0510), and basics on internet technology

Registration for Courses
  • Valid 01.08.2020-31.07.2022:


  • Applies in this implementation:

    Course assumes at least basic level of understanding on Unix-type (e.g. Linux) operating systems and programming. First exercise will be introduction to the tools.

SDG: Sustainable Development Goals

    8 Decent Work and Economic Growth


Details on the schedule
  • Applies in this implementation:

    The course has weekly lectures starting from the first period.

    There are two weekly exercises at the begining of the course. Rest
    of exercises are scheduled according to lectures. For the final
    assignment there are non-mandatory exercise sessions.


Registration and further information