Reinforcement learning approach for Advanced Sleep Modes management in 5G networks

Autor: Azeddine Gati, Eitan Altman, Tijani Chahed, Fatma Ezzahra Salem, Zwi Altman
Přispěvatelé: Département Réseaux et Services de Télécommunications (RST), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Orange Labs [Chatillon], Orange Labs, Centre National de la Recherche Scientifique (CNRS), Méthodes et modèles pour les réseaux (METHODES-SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria), Network Engineering and Operations (NEO ), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Département Réseaux et Services de Télécommunications (TSP - RST)
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Proceedings VTC-FALL 2018 : 88th Vehicular Technology Conference
VTC-FALL 2018 : 88th Vehicular Technology Conference
VTC-FALL 2018 : 88th Vehicular Technology Conference, Aug 2018, Chicago, United States. pp.1-5, ⟨10.1109/VTCFall.2018.8690555⟩
VTC-Fall
Popis: International audience; Advanced Sleep Modes (ASMs) correspond to a gradual deactivation of the Base Station (BS)'s components in order to reduce its Energy Consumption (EC). Different levels of Sleep Modes (SMs) can be considered according to the transition time (deactivation and activation durations) of each component. We propose in this paper a management solution for ASMs based on Q-learning approach. The target is to find the optimal durations for each SM level according to the requirements of the network operator in terms of EC reduction and delay constraints. The proposed solution shows that even with a high constraint on the delay, we can achieve high energy savings (almost 57% of EC reduction) without inducing any impact on the delay. When the delay constraint is relaxed, we can achieve up to almost 90% of energy savings
Databáze: OpenAIRE