Resumen
ENACT develops cutting-edge techniques and technology solutions to realise a Cognitive Computing Continuum (CCC) that can address the neds 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 and Cloud resources. The graph models are used by AI (Greaph Neuronal Networks - GNN) models and Deep Reinforcement Learning (DRL) agents to suggest the optimal deployment configurations for hyper distributed applications considering their specific needs. The AI (GNN and DRL) models are packaged as an intelligent decision-making engine that can replace the scheduling component of open-source solutions such as KubeEdge. This will enable real-time and predicitve management of distibuted infrastructure and applications. To take full advantage of the potential (compute, storage, energy efficiency, etc) opportunities in te CCC, ENACT will develop an innovative Application Programming Model (APM). The APM will support the development of distributed platform agnostic applications, capable od self-determining their optimal deployment and optimal execution configurations while taking advantage of diverse resources in the CCC. An SDK to develop APM-based distributed applications will be developed. Moreover, servicies for automatic (zero-touch provisioning-based) resource configuration and (telemetry) data collections are developed to help desing and update dynamic graph models. Enact CCC solutions will be validated in 3 use-cases with challenging resource and application requirements. International collaboration is planned as Japan Productivity Center has comminted to support with Knowledge sharing.
