SOURCE-LINKED INTELLIGENCE

Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum

CORDIS · observation · Publication date unknown

Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum MLSysOps will achieve substantial research contributions in the realm of AI-based system adaptation across the cloud-edge continuum by introducing advanced methods and tools to enable optimal system management and application deployment. MLSysOps will design, implement and evaluate a complete framework for autonomic end-to-end system management across the full cloud-edge continuum. MLSysOps will employ a hierarchical agent-based AI architecture to interface with the underlying resource management and application deployment/orchestration mechanisms of the continuum. Adaptivity will be achieved through continual ML model learning in conjunction with intelligent retraining concurrently to application execution, while openness and extensibility will be supported through explainable ML methods and an API

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recordType

award

status

SIGNED

region

EU

value

5711250

unit

EUR