Huawei Technologies Co., Limited

Omar Ahmad Mohammad Alhussein

Peter J Ashwood-Smith

Mehdi Arashmid Akhavain Mohammadi

There is provided a method and system for communication network management. There is provided an active TE architecture and procedure that rely on the epistemic uncertainty obtained from traffic forecasting models. According to embodiments, the traffic forecasting models can predict the mean of the network traffic demand and can extract one or more of the features relating epistemic uncertainty and the aleatoric uncertainty. According to embodiments, the epistemic uncertainty is used to vary the sampling frequency of network statistics in TE applications, for specific times or specific flows. A time-window can be used to predict network traffic can be varied (e.g. increased or decreased) to adjust the epistemic uncertainty.

Method and apparatus for managing network traffic via uncertainty

There are provided a method, system and computer program product for preventing unauthorized use of a deep reinforcement learning agent. The DRL agents are trained to behave as expected only when they observe the one or more required secret operational keys. In some embodiments, the DRL agents are further trained to operate at a diminished capacity when the one or more required secret operational keys are unused.

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Ottawa, Canada

Omar Ahmad Mohammad Alhussein