Network Traffic Measurement and Analysis

PhD Course

This course will focus on fundamental aspects of large-scale network traffic measurements and analysis techniques targeting two main challenges: (i) how to measure a network and (ii) how to extract knowledge from network traffic measurements. This course will start off by overviewing the most popular network measurement techniques at different layers of the communication stack: ranging from passive probes at the physical layer for wireless networks up to the Simple Network Management Protocol (SNMP) at the application layer. 


 

Building upon these tools, the course will then focus on several use cases, overviewing for each one the main building blocks of the measurement system and the specific data processing algorithms that can be used to extract knowledge from the acquired data:

- Anomaly detection and traffic identification

- Load and performance prediction in mobile radio networks


- Device profiling and classification in campus-wide WiFi networks


- User localization and behavior estimation through WiFi traffic measurements
 

 

Depending on the specific application scenario, supervised and unsupervised machine learning approaches will be studied and applied. The course will include "hands-on" lectures to implement network measurement and analysis systems.


 

Schedule

  • Tue  7/11 - 14:30 - 17:30, Room PT1
  • Fri 10/11 - 14:30 - 17:30, Room Alario (Building 21)
  • Tue 14/11 - 10:30 - 13:30, Room PT1
  • Fri 17/11 - 14:30 - 17:30, Room Alario
  • Tue 21/11 - 14:30 - 17:30, Room PT1
  • Fri 24/11 - 14:30 - 17:30, Room Alario
  • Tue 28/11 - 14:30 - 17:30, Room PT1
  • Fri 1/12 - 14:30 - 17:30, Room Alario

Course Material

Slides

Code examples

Other useful stuff