Archivio Istituzionale della RicercaWe present an overview of the application of machine learning for traffic engineering and network optimization in optical data center networks. In particular, we discuss the application of supervised and unsupervised learning for bandwidth and topology reconfiguration.
Machine-Learning-Aided Bandwidth and Topology Reconfiguration for Optical Data Center Networks / Proietti, R.; Liu, C. -Y.; Chen, X.; Ben Yoo, S. J.. - ELETTRONICO. - (2021). (Intervento presentato al convegno 2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 tenutosi a Washington, DC United States nel 6–11 June 2021) [10.1364/OFC.2021.W4A.4].
Machine-Learning-Aided Bandwidth and Topology Reconfiguration for Optical Data Center Networks
Proietti R.;
2021
Abstract
We present an overview of the application of machine learning for traffic engineering and network optimization in optical data center networks. In particular, we discuss the application of supervised and unsupervised learning for bandwidth and topology reconfiguration.
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Machine-Learning-Aided_Bandwidth_and_Topology_Reconfiguration_for_Optical_Data_Center_Networks.pdf
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OFC21_Invited_SiPh_Flexible_Data_Centers.pdf
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https://hdl.handle.net/11583/2973501