Distributed Learning for 5G-IoT
Inria
Palaiseau, Essonne
Distributed Learning for 5G-IoT
Le descriptif de l’offre ci-dessous est en Anglais
Niveau de diplôme exigé : Bac + 5 ou équivalent
Fonction : Ingénieur scientifique contractuel
A propos du centre ou de la direction fonctionnelle
The Inria Saclay-Île-de-France Research Centre was established in 2008. It has developed as part of the Saclay site in partnership with Paris-Saclay University and with the Institut Polytechnique de Paris .
The centre has 39 project teams , 27 of which operate jointly with Paris-Saclay University and the Institut Polytechnique de Paris; Its activities occupy over 600 people, scientists and research and innovation support staff, including 44 different nationalities.
Contexte et atouts du poste
The position is part of the 5G-mmTc research project aiming at deploying a 5G cellular network oriented “massive IoT”, compatible with 4G technology. The use cases are the Smart-Grid, in partnership with EDF and the connected bike, in partnership with the French Cycling Federation (FFC).
Mission confiée
As part of the project 5G-mMTC, some of the work is the orchestration and resource allocation in cellular networks, more specifically on the virtual core networks (slices) possible in 5G. The key advantage of a native 5G network is the ability to create on-demand and on-the-fly slices for each virtual operator. This allows multiple networks from distinct operators to coexist at the core of the 5GC network with heterogeneous quality of service needs, such as mMTC, URLCC, and eMBB.
Principales activités
This position focuses on the study of orchestration and resource allocation in virtual core networks (slices) of cellular networks. We will focus on the case of IoT networks such as LTE Cat-M and NB-IoT, and their 5G equivalents.
The task of the position will be to study the literature on this topic, then propose new orchestration and resource allocation algorithms, and finally implement a proof of concept through simulation. An initial objective is to perform the implementations and simulations based on the OpenAirInterface (OAI) codebase, an open-source implementation of 4G/5G base stations.
More precisely, the objective is to develop intelligent algorithms to enhance the slicing service (NSSF, "Network Slice Selection Function") and ensure efficient resource allocation. The steps will include analyzing the quality of service requirements for IoT applications, understanding the NSSF function, drafting a state of the art of related topic, developing algorithms, implementing through simulation on a free software cellular system base, and finally evaluating performance.
Compétences
- Knowledge of one or more programming languages, preferably Python and C/C++.
- Understanding of Open Air Interface
- A good command of technical English
Avantages
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
Rémunération
Income in regards to professional experience