1/3 Les informations contenues dans ce document demeurent la propriété exclusive du groupe Thales et ne doivent pas être divulguées à l'extérieur du Groupe.
D EMANDE DE
S TAGIAIRE
TUTEUR DE STAGE
Nom, Prénom Hicham Khalife / Raphaël Naves
Téléphone / E-mail 01 46 13 29 08 / Hicham.khalife@thalesgroup.com
Direction DT/THERESIS/CNS
Numéro d’imputation du stagiaire 895 135
DESCRIPTION DU STAGE Durée / Dates souhaitées 6 mois / Février 2021
Lieu du Stage Gennevilliers
Famille professionnelle 06-Logiciel
Présentation du service / Contexte
Contenu (principales missions)
The Advanced Information Technologies (TAI) laboratory at THALES is involved in cutting-edge IT projects aiming at the specification, design and integration of security and computer network infrastructures. THALES personnel has experts in several scientific fields: networking, especially for fixed and mobile IP network design, security architecture and information system. TAI is in charge of transferring technological building blocks to Thales’ business lines
Leveraging latest virtualization techniques, the newly deployed 5G network will be modular, dynamic and highly reconfigurable. In particular, for increased efficiency in communication and content distribution, deploying services at the edge of the network close to the radio interfaces (cloud RAN) is becoming a new promising trend. The technical underlying challenge is to trade between the limited available CPU and storage at the Edge from one side and the service requirements as well as the backhauling bandwidth on the other side. In brief, where, when and which service to move close to the user is the question that needs to be addressed.
In this internship, after a thorough review of the state of the art, we will investigate machine learning algorithms for mobile edge cloud. Our objective is to propose optimized algorithms capable to start or to move a particular service required by a user the closest possible to the radio antenna. To do so, the algorithm needs to optimize a number of parameters starting by the service requirements in terms throughput and delay, the user experience, the anticipated mobility, service evolution in time as well requirements of other applications in terms of hardware usage on the edge and communications on the backhaul. In this context, machine learning algorithms seem a good candidate to anticipate the service demands and the network state based on measured history.
INTITULE DU STAGE : Machine Learning for 5G virtualized RAN and Edge Cloud
THALES COMMUNICATIONS &
SECURITY
2/3 Les informations contenues dans ce document demeurent la propriété exclusive du groupe Thales et ne doivent pas être divulguées à l'extérieur du Groupe.
The candidate will have also to study the proposed architecture under standardization in 5G to implement such edge cloud solutions and implement the proposed algorithms in our 5G testbed.
PROFIL RECHERCHE Formation souhaitée
Ecoles ciblées
Ecole d'ingénieur Bac+5
Stage de fin d’études OUI NON
Compétences humaines et techniques : Outils, Langues, Logiciels …
- Mobile, core and Edge network architecture (5G) and evolutions - AI and Machine learning based algorithms, optimization techniques - NFV, Cloud Ran, SDN OpenFlow, Open vSwitch and virtualization
techniques
- Programming Languages ; C++, Python,
3/3 Les informations contenues dans ce document demeurent la propriété exclusive du groupe Thales et ne doivent pas être divulguées à l'extérieur du Groupe.
VALIDATION Demandeur :
Hicham KHALIFE Date : 19/10/2016
Accord : OUI NON
Responsable service : Nom, Prénom
Date :
Accord : OUI NON
RRH :
Nom, Prénom Date :
Accord : OUI NON
FORMULAIRE A RETOURNER COMPLETE ET VALIDE PAR MAIL A :
BRIVE fadwa.touhtouh@thalesgroup.com
BRETIGNY-SUR-ORGE laureen.malvoisin@thalesgroup.com
CHOLET helene.bourdon@thalesgroup.com
GENNEVILLIERS stagiaire-clb@thalesgroup.com
LAMBERSART valerie.ralite@thalesgroup.com
LAVAL mireille.seme@thalesgroup.com
VELIZY claire.robineau@thalesgroup.com
