Imagine your apps are like a team of workers. Instead of everyone commuting to one giant office in the city, some work from home and some work at local kiosks to be closer to the customers. This system acts as a smart manager that automatically moves these workers around based on where the demand is highest and how much electricity they use. It ensures the service stays fast and reliable without wasting energy.
Modern apps require ultra-low latency and massive data speeds that central clouds cannot provide. Companies struggle to manage the complexity of splitting their apps between central servers and local edge devices without wasting energy or breaking service agreements.
A Cloud Edge Continuum Computing Manager (CECCM) that uses AI to automate the movement and scaling of micro-services. It includes a data management layer compliant with Gaia-X standards.
If you are a fleet management provider dealing with massive data from moving vehicles—this project developed a management system that moves micro-services across the network to ensure low response times. This prevents delays in tracking and routing while saving energy consumption.
If you are an urban infrastructure operator dealing with a data deluge from thousands of street sensors—this project developed a cognitive manager that balances resources between the cloud and the far-edge. This ensures critical city services maintain their service level agreements (SLA).
If you are a smart factory integrator dealing with high-latency issues in robot control—this project developed a programmable network tool that enforces quality of service for micro-services. This allows real-time machine adjustments without the lag of a central data center.
Based on available project data, specific pricing for the end-product is not listed, as the project is funded by a EUR 5,975,000 EU contribution for research and development.
Yes, the project specifically targets a federation of resources and uses the IEEE Standard for Intercloud Interoperability to ensure it can scale across different cloud-edge infrastructures.
Based on available project data, the IP details are not specified, but the project involves 19 partners including 15 industry entities, suggesting a collaborative development model.
Yes, the data management procedures are designed to be compliant with Gaia-X and IDS approaches, using data catalogs and connectors.
The system is designed as a PaaS (Platform as a Service) and uses a three-plane architecture (user, management, and infrastructure) to facilitate integration with existing resources.
The consortium is heavily weighted toward commercial application, with 15 industry partners representing 79% of the group. This high industry ratio, combined with a presence in 10 different countries, suggests that the resulting technology is being built for immediate market needs rather than purely academic interest. The mix of 2 SMEs and larger industrial players indicates a broad target market from niche providers to large-scale infrastructure operators.
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