Gorde:
| Egile Nagusiak: | , , , , , , , , |
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| Formatua: | Recurso digital |
| Hizkuntza: | |
| Argitaratua: |
Zenodo
2026
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| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.5281/zenodo.18717877 |
| Etiketak: |
Etiketa erantsi
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Aurkibidea:
- This repository provides the ML inference engine for the ACROSS TC3.2 use case (Smart Energy-aware Zero-touch Traffic Engineering). The software predicts router power consumption from instantaneous network telemetry-derived metrics to support Network Digital Twin (NDT) environments and energy-aware traffic engineering. The inference service is containerized (Docker/Docker Compose) and uses Kafka for message exchange: it consumes input telemetry features, runs a selected ML model, and publishes predicted power consumption along with feature-based variation rates. The repository also includes a telemetry mock service to replay experiment datasets, validate predictions against ground truth, and generate verification plots. Supported router types: RA and RB. Supported model types: linear regression, polynomial regression, random forest, and deep neural networks (with optional scaling). Models are organized by router type/model type and selected dynamically via environment configuration.