Network infrastructures

Duration

30h Th, 12h Labo., 30h Proj.

Number of credits

Lecturer

Benoît Donnet, Guy Leduc, Laurent Mathy

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

This course aims at delivering a first vision of how data is processed and organized by large network organizations.  In particular, it focuses on network data collection and processing, data and network traffic management within data center (a facility composed of networked computers and storage used to organize, process, store and disseminate large amounts of data), and mobile infrastructures for delivering, e.g., multimedia content to users.
Table of Content:
Part 1: Network Data Collection and Processing (B. Donnet)

• Chap. 1: Generalities
• Chap. 2: Topology
• Chap. 3: Latency
• Chap. 4: Traffic

• Chap. 1: Data Center Network Design
• Chap. 2: Software Defined Networks
• Chap. 3: Cloud Networking

• Chap. 1: Wireless Links Characteristics
• Chap. 2: WiFi Networks
• Chap. 3: Personal Area Networks
• Chap. 4: Cellular Internet Access
• Chap. 5: Managing Mobility in IP and Cellular Networks

• Chap. 1: Audo and Video Coding Basics
• Chap. 2: Streaming Stored Video
• Chap. 3: Voice over IP
• Chap. 4: Protocols for Real-Time Conversational Applications

Learning outcomes of the learning unit

Upon completing this course, students should be aware of the importance of network data collection and processing for monitoring a large network infrastructure.  In addition, modern network infrastructures (Data center, mobile networks) must be understood in depth, as well as the way multimedia content might be delivered to end-users.

Prerequisite knowledge and skills

A good knowledge of basics of Computer Networking (INFO0010 or assimilated) is required.

Planned learning activities and teaching methods

The course is organized as follows:

• Lectures (30 hours) describing in details the theoretical and practical concepts of the course
• Lab sessions for data processing and plotting (introduction to Python libraries like Panda and Matplotlib).  Labs are done individually and a short report (a simple text file to fill in) must be completed by the end of the lab
• Several assignments to be done in teams of 2 students.

Mode of delivery (face-to-face ; distance-learning)

The face-to-face lectures are complemented by lab sessions, an introduction to Python libraries (Panda, Matplotlib) and several seminars.  Assignments are carried out remotely.
The course is entirely given in English.

Recommended or required readings

Slides, labs and assignments subjects will be made available on the course web page
Following books have been used for building the course:

• M. Crovella, B. Krishnamurthy.  Internet Measurement: Infrastructure, Traffic, and Applications.  Wiley.  July 2006.
• J. Kurose, K. Roth. Computer Networking: A Top-Down Approach, 7th edition, 2016. An identical version is published by Pearson Education.

Assessment methods and criteria

Work placement(s)

Organizational remarks

The course is organized during the second term (from February to mid-May).
The course is not organized in 2018-2019.

Contacts

Professors:

• B. Donnet (benoit.donnet@uliege.be - office 1.15/B28)
• G. Leduc (guy.leduc@uliege.be - office 1.73a/B28)
• L. Mathy (laurent.mathy@uliege.be - office 1.15/B37)

Items online