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Multi-Step Traffic Prediction for Multi-Period Planning in Optical Networks
- Publication Year :
- 2024
-
Abstract
- A multi-period planning framework is proposed that exploits multi-step ahead traffic predictions to address service overprovisioning and improve adaptability to traffic changes, while ensuring the necessary quality-of-service (QoS) levels. An encoder-decoder deep learning model is initially leveraged for multi-step ahead prediction by analyzing real-traffic traces. This information is then exploited by multi-period planning heuristics to efficiently utilize available network resources while minimizing undesired service disruptions (caused due to lightpath re-allocations), with these heuristics outperforming a single-step ahead prediction approach.
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2404.08314
- Document Type :
- Working Paper