PhD Studentship - AI-Driven Energy Optimization in NextGeneration RANs

Research Group / Department / School: School of Computer Science and Statistics, Trinity College Dublin, the University of Dublin 

Location: Discipline of Networks and Distributed Systems, School of Computer Science and Statistics, Trinity College Dublin, the University of Dublin College Green, Dublin 2, Ireland 

Reports to: Dr. Merim Dzaferagic 

Hours of Work: 39

Post Summary 

The disaggregation of Radio Access Networks (RANs) introduces new challenges in energy management. Unlike traditional architectures with static power allocation, disaggregated RANs allow for dynamic scaling and flexible placement of network functions, which significantly impacts power consumption. Initial research has shown that the placement of network functions, along with their scaling up and down, plays a critical role in overall energy efficiency. However, there is a significant gap in real-world experimentation and data collection, particularly in an end-to-end network deployment that integrates AI-driven energy optimization strategies. 

Key challenges include collecting relevant energy consumption data, understanding its correlation with network performance, and developing AI-driven power management strategies that dynamically adapt to traffic demands. The project will involve hands-on experimentation with real networking equipment in the OpenIreland testbed, enabling the validation of AI-based techniques in a live disaggregated network environment. By evaluating the impact of function placement and scaling on power efficiency, the research will quantify trade-offs between energy savings and network performance under different AI-driven approaches. 

The expected outcomes include a better understanding of how disaggregated network architectures influence power consumption, along with the development of AI-driven energy optimization techniques tailored for real-world deployments. By integrating experimental insights from OpenIreland, this project will bridge the gap between theoretical energy models and practical network operation, paving the way for more efficient and adaptable next generation mobile networks.

Standard Duties and Responsibilities of the Post 

This is a full-time 4-year structured PhD project, based in the Discipline of Networks and Distributed Systems at Trinity College Dublin.

Qualifications 

Applicants should have (or expect to obtain before the project starts) at least a 2.1 Honours degree or an equivalent qualification in electrical engineering, computer engineering, or computer science.