Presenting the COGNIFOG Framework: Architecture, Building Blocks and Road toward Cognitive Connectivity
Toni Adame1, Emna Amri2, Grigoris Antonopoulos3
1Fundació i2CAT, Gran Capità 2-4, 08034 Barcelona, Spain.
COGNIFOG, a new cognitive fog framework, uses AI for autonomous IoT-edge-cloud operations. Early tests show improved network resource use, enhancing efficiency and reliability in computing environments.
Area of Science:
- Computer Science
- Distributed Computing
- Artificial Intelligence
Background:
- Ubiquitous computing demands real-time processing, security, and energy efficiency.
- Fog computing brings resources closer to data sources but faces challenges in heterogeneous environments.
- Resource allocation, management, security, and connectivity are key issues in fog computing.
Purpose of the Study:
- Introduce COGNIFOG, a novel cognitive fog framework.
- Enable autonomous operation, adaptability, and scalability across the IoT-edge-cloud continuum.
- Enhance efficiency and reliability in next-generation computing environments.
Main Methods:
- Leveraging intelligent, decentralized decision-making processes.
- Utilizing machine learning algorithms and distributed computing principles.
- Integrating cognitive capabilities for autonomous management.
Main Results:
- Preliminary results show promising improvements in network resource utilization.
- Demonstrated enhanced efficiency in a real-world IoT scenario using connectivity-focused COGNIFOG blocks.
- Indicated potential for increased reliability and seamless physical-digital integration.
Conclusions:
- COGNIFOG offers a promising approach to address fog computing challenges.
- The framework's cognitive capabilities are expected to boost efficiency and reliability.
- Further development aims to enhance intelligence, resilience, and adaptability for evolving computing demands.
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