Imagine your smart devices could instantly decide whether to process data locally or send it to a powerful cloud based on how much energy they have left. It is like having a smart traffic controller for data that automatically moves tasks to the best available spot to save power and time. This ensures your apps stay fast and secure without you having to manage the complex hardware behind the scenes.
Companies struggle with high latency, energy waste, and lack of control when relying on centralized cloud providers for edge device data. They need a way to run complex code across diverse hardware without managing every single device manually.
An AI-enabled serverless platform including a Device Client, Provisioning Engine, and a Serverless Runtime. It also includes 'cognit-ops-forge' for automated deployment to cloud or on-premise environments.
If you are a grid operator dealing with fluctuating energy costs and carbon emissions — this project developed a power-grid aware adaptation system that uses predictive analytics to place workloads where they are most energy-efficient.
If you are a factory owner dealing with slow response times from distant cloud servers — this project developed a distributed function execution system that allows computationally-intensive processing to happen closer to your sensors and actuators.
If you are a device maker dealing with limited battery life and hardware constraints — this project developed a serverless runtime that abstracts complex infrastructure, allowing your devices to access high-performance computing without heavy local overhead.
Based on available project data, specific pricing is not mentioned, but the project utilizes open source repositories and aims to reduce costs for developers by optimizing resource use.
Yes, the project is designed for the cloud-edge continuum and includes a 'cognit-ops-forge' tool for automatic deployment on-premise or in the public cloud.
The project mentions that source code is hosted in open source repositories accessible via public URLs.
The system includes a mechanism to monitor and optimize infrastructure across multiple cloud and edge providers through an abstraction layer.
The project period runs from 2023-01-01 to 2025-12-31, indicating it is currently in the development and validation phase.
The consortium is heavily industry-weighted with a 60% industry ratio, comprising 6 companies (including 3 SMEs) and 4 research/academic partners across 6 European countries. This balance suggests a strong focus on commercial viability and practical application rather than purely theoretical research, led by a specialized SME (OpenNebula Systems).
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