Adaptive Scheduling and Deployments of Data Intensive Workloads on Energy Efficient Edge to Cloud Continuum
ENACT develops cutting-edge techniques and technology solutions to realise a Cognitive Computing Continuum (CCC) that can address the needs for optimal (edge and Cloud) resource management and dynamic scaling, elasticity, and portability of hyper-distributed data-intensive applications. At infrastructure level, the project brings visibility to distributed edge and Cloud resources by developing Dynamic Graph Models capable of capturing and visualising the real-time and historic status information, connectivity types, dependencies, energy consumption etc. from diverse edge and Cloud resources. The graph models are used by AI (Graph Neural Networks – GNN) models and Deep Reinforcement Learning (DRL) agents to suggest the optimal deployment configurations for hyper distributed applications considering their specific needs.
