Título:
LQ-GNN: A Graph Neural Network model for response time prediction of microservice-based applications in the computing continuum.
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Autor:
Richart, Matías
Gorricho, Juan-Luis
Baliosian, Javier
Contreras, Luis M.
Muniz, Alejandro
Serrat, Joan
Gorricho, Juan-Luis
Baliosian, Javier
Contreras, Luis M.
Muniz, Alejandro
Serrat, Joan
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Tipo de documento:
Artículo
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Palabras clave:
Computing Continuum
Elasticity
Microservicebased applications
Graph Neural Networks
Machine Learning
Elasticity
Microservicebased applications
Graph Neural Networks
Machine Learning
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Año de publicación:
2025
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Resumen:
To address the challenges posed by the deployment of microservices of future end-user applications in the cloud continuum, a performance prediction model working together with a network elasticity controller will be needed. With that aim, this work introduces Layered Queuing-Graph Neural Networks (LQ-GNN), a novel Machine earning (ML) approach to develop a generalized performance prediction model for microservicebased plications. Unlike previous works focused on individual applications, our proposal aims for a versatile model applicable to any microservice-based application, integrating the Layered Queueing Network (LQN) modeling with Graph Neural Networks (GNN). LQ-GNN allows to efficiently estimate the response time of applications under different resource allocations and placements on the computing continuum. The obtained evaluation results indicate that the roposed model achieves a prediction error below 10% when considering different evaluation scenarios. Compared to existing methodologies, our approach balances prediction accuracy and computational efficiency, making it viable for real-time deployments. Consequently, ML-based performance prediction can significantly enhance the resource management and elasticity control of microservice-based architectures, leading to more resilient and efficient systems.
Descripción:
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Editorial:
IEEE
EN:
IEEE Transactions on Parallel and Distributed Systems, pp. 1-12.
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Citación:
Richart, M., Gorricho, J., Baliosian, J., y otros. "LQ-GNN: A Graph Neural Network model for response time prediction of microservice-based applications in the computing continuum". IEEE Transactions on Parallel and Distributed Systems. [en línea] 2025, pp. 1-12. DOI: 10.1109/TPDS.2025.3564214.
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Licencia Creative Commons Atribución (CC - By 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| RGBCMS25.pdf | Versión aceptada | 5.32 MB | Adobe PDF |