Network Intelligence and Communication Services

Catalog of Télécom SudParis courses

Code

IGFE NET 7012

Level

M2

Graduate

Graduate

Semester

Fall

Domain

Réseaux

Program

Programme Ingénieur

Language

Anglais/English

ECTS Credits

4

Class hours

48

Program Manager(s)

Department

  • Réseaux et Services Multimédia Mobiles

Organisation

Cours/TD/TP/projet/examen :

Learning objectives

The coursework introduces students to Next Generation Services, with a focus on Service architectures. The course describes in detail how communication services are conceived, developed and deployed in wireline and wireless networks.

The course concentrates on NGN (Next Generation Networks) architectures. The courses also address the webification of services (from the IMS to OTT solutions ) that will significantly change the telecommunication industry worldwide with the replacement of today’s networks.

The course also cover today’s networks, to allow the students understand the changes that the world of telecommunications and internet is facing. Message flows and procedures are thoroughly examined in class and in small student groups to strengthen understanding. CAMEL-based service architectures, IMS/NGN service architectures are particularly emphasized.

Network Intelligence course encompasses four main parts. The first part of the course aims to present the background on Autonomic computing and Networking as a core stone of Network intelligence. The Second part objectives are to zoom on the algorithmic part, the possible operations (classification, clustering, etc.). The third and fourth part target to practice the of machine learning for network data (data extraction, pre-processing, model set-up, configuration and validation, etc.)

In cooperation with Orange Labs and CISCO.

Content

Introduction to Network cognitive management
- Motivation
- Architecture
- Network Data
- Analytics and SDN & NFV
Zoom on machine learning algorithms for Network
- Basics
- Neural Network and deep learning algorithms
- Approach and process for ML in Networks
Tools, libraries and Hands-on (python based)
- Basics for a machine learning project set up, tools, manipulation of opensource dataset
- Network focused Hands-on (python based)
- Preprocessing of Network data:
- Model selection; Model execution; Model validation

From Telcos to WebCos
- SIP
- IMS, NGN architecture
- Service architecture
- Web-NGN convergence,
- SDN (Software Defined Networking)
- NFV (Network Function Virualisation)

Evaluation

Evaluation: Group work and oral presentation.