Aug 5, 2021 · The evaluation results show that the proposed hybrid DRL-heuristic approach is more robust and reliable in case of unpredictable network load changes than pure ...
Mar 29, 2022 · In this paper, we propose to evaluate the robustness of online learning for optimal network slice placement.
Jul 1, 2022 · In this paper, we propose to evaluate the robustness of online learning for optimal network slice placement. A major assumption in this study is ...
Jan 24, 2023 · In this paper, we propose to evaluate the robustness of online learning for optimal network slice placement.
We consider online learning for optimal network slice placement under the assumption that slice requests arrive according to a non-stationary Poisson process.
Slices are placed on a substrate network, referred to as Physical Network Substrate (PSN) and described in Section III-A. Slices give rise to Network Slice ...
On the Robustness of Controlled Deep Reinforcement Learning for Slice Placement. Authors. Alves Esteves, Jose Jurandir; Boubendir, Amina; Guillemin, Fabrice ...
On the Robustness of Controlled Deep Reinforcement Learning for Slice Placement ; Journal: Journal of Network and Systems Management, 2022, № 3 ; Publisher: ...
Mar 29, 2022 · We consider online learning for optimal network slice placement under the assumption that slice requests arrive according to a non-stationary ...
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On the robustness of controlled deep reinforcement learning for slice placement. JJ Alves Esteves, A Boubendir, F Guillemin, P Sens. Journal of Network and ...