MAGNET: An optimized DevOps framework for efficient software integration and orchestration in the IoT-Edge-Cloud Continuum

This paper introduces MAGNET, a DevOps framework comprising Continuous Integration/Continuous Deployment practices, alongside flexible development and integration infrastructures, as applied in COGNIFOG, an innovative computing ecosystem currently under development that uses decentralized decision m...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2025 6th International Conference in Electronic Engineering & Information Technology (EEITE) s. 1 - 6
Hlavní autori: Agorogiannis, Evangelos, Petrakis, Kostas, Antonopoulos, Grigorios, Anagnostopoulos, Themistoklis, Grigoropoulos, Nasos, Benomar, Zakaria
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 04.06.2025
Predmet:
CI/CD
cognitive connectivity
Complexity theory
DevOps
Ecosystems
Edge computing
fog computing
IoT
IoT-edge-cloud continuum
Scalability
Security
service orchestration
Smart cities
Smart manufacturing
Software
Testing
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:This paper introduces MAGNET, a DevOps framework comprising Continuous Integration/Continuous Deployment practices, alongside flexible development and integration infrastructures, as applied in COGNIFOG, an innovative computing ecosystem currently under development that uses decentralized decision making, machine learning, and distributed computing to enhance autonomy, adaptability, and scalability within the IoT-edge-cloud continuum. The proposed approach ensures efficient, reliable, and seamless framework integration, offering key insights into integration architecture, data flow management, and the adoption of advanced technologies. This work demonstrates the efficiency and adaptability of the COGNIFOG ecosystem through three real-world trials in smart cities, e-health, and smart manufacturing, along with the creation of a comprehensive QuickStart Guide for deployment, offering a robust solution for the complexities of next-generation computing environments.
DOI:10.1109/EEITE65381.2025.11166038