VNF placement in 5G Networks using AI/ML
La transition inévitable des dispositifs matériels physiques vers des modules logiciels légers et réutilisables dans le cadre de la virtualisation des fonctions de réseau (NFV) offre d’innombrables possibilités tout en présentant plusieurs défis sans précédent.
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Online Service Function Chain Planning for Satellite-Ground Integrated Networks to Minimize End-to-End (E2E) Delay. [PDF]
Kim S, Park J, Youn J, Ahn S, Cho S.
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Neurostimulation Methods in the Treatment of Depression: A Comparison of rTMS, tDCS, and Venlafaxine Using a Pooled Analysis of Two Studies. [PDF]
Hejzlar M, Novak T, Bares M.
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Hybrid GA-PSO Optimization for Controller Placement in Large-Scale Smart City IoT Networks. [PDF]
Memon SA +11 more
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Load-Balanced Dynamic SFC Migration Based on Resource Demand Prediction. [PDF]
Sun T, Hu H, Zhang S.
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Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey. [PDF]
Hurtado Sánchez JA +2 more
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SFC active reconfiguration based on user mobility and resource demand prediction in dynamic IoT-MEC networks. [PDF]
Guo S, Liu L, Jing T, Liu H.
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Validating a 5G-Enabled Neutral Host Framework in City-Wide Deployments. [PDF]
Fernández-Fernández A +9 more
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Evaluation and optimization of resource matching for perception services in power communication networks. [PDF]
Wei L, Shang L, Zhang M, Li H, Zhu X.
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Utility-Driven End-to-End Network Slicing for Diverse IoT Users in MEC: A Multi-Agent Deep Reinforcement Learning Approach. [PDF]
Ejaz MA +4 more
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