All Projects
Digital TwinMECHetNet

Digital Twin-enabled MEC for Heterogeneous Networks

Digital twins provide a real-time virtual replica of physical network infrastructure, enabling predictive optimization, what-if analysis, and proactive failure recovery. This project developed a lightweight digital twin platform tailored for mobile edge computing in heterogeneous IoT networks, enabling operators to simulate and optimize multi-service deployments without disrupting live operations.

Research Objectives

  • Construct accurate digital twin models for MEC servers and IoT end-devices
  • Enable real-time synchronization between physical and virtual network states
  • Use digital twin simulations to pre-optimize task offloading and resource allocation policies
  • Validate twin fidelity under dynamic network conditions and device mobility

Methods & Techniques

  • Model-based systems engineering for twin construction
  • Online learning for adaptive twin state synchronization
  • Deep Q-Network (DQN) for offloading policy optimization within the twin
  • Trace-driven simulation using real IoT traffic datasets

Interested in this research?

Get in touch to discuss collaboration or graduate opportunities.

Contact Dr. Hossain