EURECOM’s Communication System Department invites applications for a PhD position (M/F) in the area of Named Knowledge Networking (NKN) in the context of cooperative connected automated mobility (CCAM).
Vehicular networks evolved from exchanging data between vehicles to information generated by vehicles. With the recent popularity and impact of AI mechanisms either to improve vehicular network itself or being used for CCAM directly, vehicular networks need to again evolve to exchange and share knowledge between vehicles. In a previous study, we formulated a conceptual framework for Vehicular Knowledge Networking1 and focused on vehicular knowledge creation and naming, leading to a first semantic description of AI models.
The objective of this position is to extend this work, focusing this time on networking aspects. The goal is to model and analyze the impact of NKN to locate, store and efficiently retrieve knowledge in vehicular networks. Information-centric mechanisms, such as Named Data Networking (NDN), Named Function Networking (NFN) or Named AI Networking are expected to be key promising mechanisms to be investigated. Distributed storage/caching as well as distributed ledger technologies are also expected to be complementary mechanisms to support NKN.
The work will be carried out in cooperation with an automotive industrial partner, the candidate will have the opportunity to closely interact with it.
Specifically, the focus of this position will be around the topics of: (i) abstraction, modelling and analysis of networking mechanisms to locate and retrieve knowledge, (ii) methodology for optimal knowledge storage according to its context, (iii) investigate pertinent solutions to secure the creation, exchange and sharing of knowledge.
Finally, this thesis has also an experimental aspect. First, the evaluation of NKN will be conducted on simulators adapted to CCAM. As function of the pertinence, NKN integration in a 5G architecture could be envisioned and evaluated on the EURECOM experimental 5G platforms OpenAirInterface.
- Education Level / Degree : Master-level degree or equivalent
- Field / specialty: Computer Science , Electrical or Telecommunication Engineering
- Technologies: A very good background in Wireless and/or Wired Networks (IP, 5G). Very good analyticalskills is highly appreciated. Knowledge in AI as well as semantics is appreciated.
- Languages / systems: Experience in C++ or Python programming. Knowledge in simulators (ns-3,Omnet++) is highly appreciated.
- Other skills / specialties: knowledge in C-ITS or Information-centric networks
- Other important elements: Strong communication skills and keen
The application must include:
- Detailed curriculum,
- Motivation letter of two pages also presenting the perspectives of research and education,
- Name and address of three references.
Applications should be submitted by e-mail to email@example.com with the reference : CS/JH/NKN/0622
- Screening will start immediately.
- Deadline to apply: ASAP but no later than June 30th 2022
Start date: ASAP
Duration: Duration of the thesis