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Machine-Learning-Aided Bandwidth and Topology Reconfiguration for Optical Data Center Networks

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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.

© 2021 The Author(s)

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