Durée
30h Th, 12h Labo., 30h Proj.
Nombre de crédits
Enseignant
Langue(s) de l'unité d'enseignement
Langue anglaise
Organisation et évaluation
Enseignement au premier quadrimestre, examen en janvier
Horaire
Unités d'enseignement prérequises et corequises
Les unités prérequises ou corequises sont présentées au sein de chaque programme
Contenus de l'unité d'enseignement
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)
Acquis d'apprentissage (objectifs d'apprentissage) de l'unité d'enseignement
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.
Savoirs et compétences prérequis
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.
Activités d'apprentissage prévues et méthodes d'enseignement
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 d'enseignement (présentiel, à distance, hybride)
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.
The course is not given in 2020-2021.
Adaptations organisationnelles liées au contexte sanitaire
Lectures recommandées ou obligatoires et notes de cours
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.
Modalités d'évaluation et critères
Vous trouverez ci-dessous les modalités d'évaluation envisagées pour les examens en présentiel et à distance ainsi que celle souhaitée en cas de session hybride. En fonction de l'évolution sanitaire, la modalité choisie vous sera communiquée au plus tard un mois avant le début de la session d'examen.
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.
Stage(s)
Remarques organisationnelles
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
Notes en ligne
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.