Multi-Step Traffic Prediction for Multi-Period Planning in Optical Networks
<|reference_start|>Multi-Step Traffic Prediction for Multi-Period Planning in Optical Networks: 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.<|reference_end|>
@article{maryam2024multi-step,
    title={Multi-Step Traffic Prediction for Multi-Period Planning in Optical
  Networks},
    author={Hafsa Maryam, Tania Panayiotou, Georgios Ellinas},
    journal={arXiv preprint arXiv:2404.08314},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.08314},
    primaryClass={cs.NI cs.LG}
}