PhD " API-based approach for E2E green connected mobility " F/M - Belfort, France - Orange Business Services

Description

about the role

Your role is to conduct research on the complex resolution of end-to-end energy optimization in vehicular networks involving vehicles, base stations, Cloud/Edge networks, and AI models.

Global Context and Problem Statement
In a world transitioning towards more sustainable and connected solutions, the emergence of connected green mobility represents a major challenge. This evolution is driven by the need to reduce greenhouse gas emissions while offering efficient and integrated transportation solutions. The research context is based on the increasing demand for energy optimization in 5G-V2X networks, resulting from the convergence of telecommunications technologies and connected vehicles. The central problem lies in the complex management of energy consumption across various network elements and vehicles, while ensuring optimal performance. Thus, there is a need to develop innovative strategies to minimize energy consumption while maintaining high service levels.

Scientific Objective – Results and Challenges to Address
The objective of the thesis is to develop an API-based approach for connected green mobility, aiming to optimize energy efficiency throughout the vehicle's journey using AI models capable of accurately predicting energy consumption in green V2X networks, considering operational and mobility constraints. This involves addressing challenges such as modeling energy consumption patterns, optimizing AI algorithms for precise consumption prediction, and seamlessly integrating mobility services into existing infrastructure. Expected results include the design of innovative models and the identification of key parameters influencing energy consumption for scalable connected green mobility. This will guide future energy optimization strategies, and ultimately, the exposure of these results through APIs.

References

[1] Ilhem Souissi, Rihab Abidi, Nadia Ben Azzouna, Tahar Berradia, Lamjed Ben Said, « ECOTRUST: A novel model for Energy COnsumption TRUST assurance in electric vehicular networks », Ad Hoc Networks, Volume 149, 2023,

[2] B. Mao, F. Tang, Y. Kawamoto and N. Kato, "AI Models for Green Communications Towards 6G," in IEEE Communications Surveys & Tutorials, vol. 24, no. 1, pp , First quarter 2022, doi: /COMST

[3] Lv, Zhihan, and Wenlong Shang. "Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review." Green Technologies and Sustainability

about you

Proven skills and experience in Data Science.

Good knowledge of languages associated with Machine Learning techniques (R, ).

Strong knowledge and expertise in telecommunications networks.

Solid understanding of 3GPP cellular networks, including 5G and 6G networks.

Strong interest in research and innovation, accompanied by curiosity and creativity.

Autonomous, motivated for innovation, and enjoys teamwork.

Ability to address complex problems and propose innovative solutions.

Rigorous, strong analytical, and synthesis skills.

Ability to work in an international environment and communicate effectively in written and oral form. Able to vulgarize your work to make it understandable to a wide audience, and you enjoy persuading others.

Advanced level in French and English (document writing, presentations, meeting facilitation, ).

Master of Science or Engineering Degree in computer science, telecommunications, or mathematics

Experience or internship in research-oriented Data Science will be a plus.

additional information

This PhD will provide you with the expertise of Orange, an international group and expert in the field of information and communication technologies. You will work in an international context with the opportunity to contribute to research projects with external partners from academic and industrial environments.

You will study new mechanisms based on the analysis of real data from vehicular mobile traffic and based on machine learning algorithms, in order to estimate and optimize the energy consumption of a vehicular network ecosystem.

department

Orange Innovation brings together the research and innovation activities and expertise of the Group's entities and countries. We work every day to ensure that Orange is recognized as an innovative operator by its customers, and we create value for the Group and the Brand in each of our projects. With 740 researchers, thousands of marketers, developers, designers and data analysts, it is the expertise of our 6,000 employees that fuels this ambition every day.

Orange Innovation anticipates technological breakthroughs and supports the Group's countries and entities in making the best technological choices to meet the needs of our consumer and business customers.

Within Innovation, you will be integrated into a research team from DATA & AI entity at the forefront of innovation and expertise focused on harnessing advanced artificial intelligence techniques implemented across a diverse range of applications, including optimization and automation of mobile/vehicular network management.

contract

Thesis