All Outputs (2)

Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks (2025)
Presentation / Conference Contribution
Dua, A., Jindal, A., Singh Aujla, G., & Sun, H. (2025, June). Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

6G applications rely on data-intensive AI models for network optimization. These demand a scalable and energy-efficient framework to handle massive device networks with stringent latency requirements which current solutions struggle to support. Even... Read More about Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks.

Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum (2024)
Presentation / Conference Contribution
Dua, A., Singh Aujla, G., Jindal, A., & Sun, H. (2024, December). Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum. Presented at IEEE Global Communications Conference - Workshop on Next-Gen Healthcare Fusion (NgHF): AI-driven Secure Integrated Networks for Healthcare IoT Systems, Cape Town, South Africa

The increasing demand for machine learning (ML) technologies has led to a significant rise in energy consumption and environmental impact, particularly within the context of distributed computing environments like the Edge-Fog-Cloud Continuum. This p... Read More about Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum.