A Reference Architecture for Cloud-Edge Meta-Operating Systems Enabling Cross-Domain, Data-Intensive, ML-Assisted...

Area of Science:

• Computer Science
• Distributed Systems
• Edge Computing

Background:

• Current hierarchical architectures struggle with the data explosion from IoT proliferation.
• Intelligent applications require seamless coordination across cloud, edge, and IoT devices.
• Existing solutions offer only partial support for the cloud-to-edge-to-IoT continuum.

Purpose of the Study:

• To present a reference architecture for a meta-operating system (RAMOS).
• To enable a dynamic, distributed, and trusted continuum for next-generation edge applications.
• To facilitate secure data placement at the origin and support heterogeneous environments.

Main Methods:

• Development of a layered reference architecture for RAMOS.
• Detailed description of RAMOS building blocks and their interconnections.
• Illustration of RAMOS in five practical application scenarios.

Main Results:

• RAMOS architecture supports domain-agnostic and heterogeneous device integration.
• The system ensures secure and trusted data placement at the data source.
• Demonstrated applicability in industrial and societal scenarios focusing on distributed intelligence and privacy.

Conclusions:

• RAMOS provides a robust framework for advanced edge computing applications.
• The architecture promotes distributed intelligence, privacy preservation, and environmental footprint minimization.
• RAMOS has significant business potential within an open edge ecosystem and contributes to climate net neutrality.