Duration
30h Th, 12h Labo., 30h Proj.
Number of credits
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
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), wireless and mobile networks, and infrastructures for multimedia content delivery 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
Part 3: Wireless and Mobile Networks (G. Leduc)
Part 4: Multimedia Applications (G. Leduc)
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, as well as basics in Statistics (MATH0487 or MATH7370 or assimilated).
Being comfortable with programming (e.g., Python) is also suitable.
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 (3 sessions over the semester) are supervised practical sessions. Students are expected to prepare, at home, those sessions by making sure all requirements are installed on their own computer. Labs are done individually and a short report (simple text file to fill in and/or piece of code) must be completed by the end of the lab session.
- Assignments by teams of 2 students (2 assignments over the semester). Assignments are larger problems to be solved
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
Students are graded in two ways: continuous evaluation (45% of the final grade) and oral exam (55% of the final grade).
Continuous Evaluation
During the semester, students will be evaluated several times through practical sessions:
- Lab reports. Several labs are organized during the semester and are graded (15% of the final grade) through reporting (a simple text file to fill in during/just after the lab with student's answers).
- Assignments. Assignments are organized during the semester and are graded (30% of the final grade). Assignments will focus on Part 1 (Network Data Collection and Processing) and Part 2 (Data Center) of the course.
Presence at the labs is mandatory. Attending all labs and doing all assignements is required for attending the oral exam. In case of lab absence and/or assignement not provided, the student will receive an "Absence" grade (and automatically be postponed to the resit).
Oral Exam
The oral exam (on the theoretical part of the course) accounts for 55% of the final grade.
The oral exam will focus on Part 2 ¿ Part 4 of the course (i.e., Part 1, Network Data collection and Processing, will not be part of the oral exam)
Resit
In case of failure in June, students must improve their assignements for the resit (deadline 1st day of the resit session) if the grade was below 10/20. This must be done individually (note that no support will be provided, either by the TA or the lecturers, during summer). Labs cannot be redone.
If the grades of the labs are favorable to the students, the resit session is identical to the first one, with the same weighting. On ther other hand, if the labs grades are not not favorable to the student, it will not be taken into account in the weighting in September.
Oral exam must be redone.
Work placement(s)
Organizational remarks
The course is organized during the first term (from mid-September to end of December), on Friday afternoon. All lectures are in English.
Contacts
Professors:
- Benoit Donnet (benoit.donnet@uliege.be - office 1.15/B28)
- Guy Leduc (guy.leduc@uliege.be - office 1.73a/B28)
- Laurent Mathy (laurent.mathy@uliege.be - office 1.15/B37)
- Sami Ben Mariem
- Cyril Soldani: cyril.soldani@uliege.be
Adaptation of teaching commitments following the COVID-19 pandemic for the May-June 2020 session
Teaching methods implemented : distance-learning
The course was given during the 1st semester. No adjustment is required with respect to June session.
Assessment subjects
The course was given during the 1st semester. No adjustment is required with respect to June session.
Assessment methods
The course was given during the 1st semester. No adjustment is required with respect to June session.
Contacts
Professors:
- Benoit Donnet (email) -- Office 1.15/B28
- Guy Leduc (email) -- Office 1.73a/B28
- Laurent Mathy (email) -- Office 1.15/B37
- Sami Ben Mariem (email) -- Office
- Cyril Soldani (email) -- Office 1.10/B37
Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session
Assessment subjects
In case of failure in June, students must improve their assignements for the resit (deadline 1st day of the resit session) if the grade was below 10/20. This must be done individually (note that no support will be provided, either by the TA or the lecturers, during summer). Labs cannot be redone.
If the grades of the labs are favorable to the students, the resit session is identical to the first one, with the same weighting. On ther other hand, if the labs grades are not not favorable to the student, it will not be taken into account in the weighting in September.
Oral exam must be redone (remotely, through a WebEx session).
Assessment methods
The oral exam will be organized remotely, using Webex (approximately 30min, with G. Leduc only).
No headphones allowed during the oral exam (WebEx is able to manage automatically echo issues)
Contacts
Lecturers:
- Benoit Donnet
- Guy Leduc
- Laurent Mathy
- Sami Ben Mariem
- Cyril Soldani
Items online
Course Web Site
The course web site contains PDF of the slides, labs/assignments subjects, details about gradings, and the course agenda. It also allows students to interact with the Pedagogical Team through the Discussion forum.