PEDAL
An AI pedagogical engine for language education that embeds task-based teaching and CEFR-aligned progression, not just AI-generated content.
University College Dublin
Lead: Prof. Alessandro Benati
Digital InfrastructureOptimises how 6G networks allocate computing resources at the edge, so demanding services like autonomous vehicles run reliably on constrained hardware.

With 35 billion IoT devices expected by 2028, the upcoming 6G era aims to support innovations such as autonomous vehicles, connected healthcare, and industrial automation. However, scaling these services at the network edge presents critical challenges. Virtual Network Functions (VNFs)—responsible for both end-user apps and core network services—must operate efficiently on resource-constrained edge devices.Existing reinforcement learning-based orchestration techniques often fail to model complex system correlations and lack scalability.
The key objectives of 6Gorch are:
1. Optimising joint resource orchestration for extreme edge environments.
2. Directly supporting 6G goals, addressing key limitations in current orchestration models.
3. Enabling scalable, low-latency orchestration capable of adapting to dynamic network conditions in real time.
Last updated: 25 September 2026

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