Objectives

• Optimize wireless networks for the synchronization of Digital Twins (DTs) by managing network resources dynamically.
• Investigate adaptive algorithms leveraging AI and reinforcement learning to improve network performance.

Methodology

• Model the resource allocation problem in wireless networks for DT synchronization, identifying key performance indicators (latency, jitter, packet loss).
• Implement representative scenarios using network and digital twin simulation tools (e.g., NS-3, OMNeT++).

Expected Contributions

• A novel adaptive resource allocation framework capable of adjusting in real time to varying conditions.
• Guidelines for integrating adaptive resource allocation into industrial DT deployments.

For applications, please send your CV and cover letter to lemia.louail@univ-lorraine.fr.