Cargando…

Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey

Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving 5G and 6G networks. A 5G/6G network can comprise various network slices from unique or multiple tenants. Network providers need to perform intelligent and efficient resource management to offer slices that meet th...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hurtado Sánchez, Johanna Andrea, Casilimas, Katherine, Caicedo Rendon, Oscar Mauricio
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032530/ https://www.ncbi.nlm.nih.gov/pubmed/35459015 http://dx.doi.org/10.3390/s22083031

Ejemplares similares

Two Tier Slicing Resource Allocation Algorithm Based on Deep Reinforcement Learning and Joint Bidding in Wireless Access Networks
por: Chen, Geng, et al.
Publicado: (2022)

Model-Based Reinforcement Learning with Automated Planning for Network Management
por: Ordonez, Armando, et al.
Publicado: (2022)

5G Network Slicing: Methods to Support Blockchain and Reinforcement Learning
por: Hu, Juan, et al.
Publicado: (2022)

Deep reinforcement learning for wireless networks
por: Yu, F Richard, et al.
Publicado: (2019)

Resource-Efficient Sensor Data Management for Autonomous Systems Using Deep Reinforcement Learning
por: Jeong, Seunghwan, et al.
Publicado: (2019)

Implementation of Trusted Traceability Query Using Blockchain and Deep Reinforcement Learning in Resource Management
por: Jiang, Yunting, et al.
Publicado: (2022)

Deep Reinforcement Learning-Based Resource Allocation for Cellular Vehicular Network Mode 3 with Underlay Approach
por: Fu, Jinjuan, et al.
Publicado: (2022)

Deep Reinforcement Learning Based Resource Allocation for D2D Communications Underlay Cellular Networks
por: Yu, Seoyoung, et al.
Publicado: (2022)

A Graph Convolutional Network-Based Deep Reinforcement Learning Approach for Resource Allocation in a Cognitive Radio Network
por: Zhao, Di, et al.
Publicado: (2020)

Deep Reinforcement Learning-Empowered Resource Allocation for Mobile Edge Computing in Cellular V2X Networks
por: Li, Dongji, et al.
Publicado: (2021)

Deep Reinforcement Learning for Attacking Wireless Sensor Networks
por: Parras, Juan, et al.
Publicado: (2021)

Application of deep neural network and deep reinforcement learning in wireless communication
por: Li, Ming, et al.
Publicado: (2020)

A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation
por: Han, Dong, et al.
Publicado: (2023)

Deep learning representations to support COVID-19 diagnosis on CT slices
por: Ruano, Josué, et al.
Publicado: (2022)

Slicing with deep learning models at ProtoDUNE-SP
por: Rossi, M
Publicado: (2023)

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning
por: Zhang, Yue, et al.
Publicado: (2016)

Federated Deep Reinforcement Learning-Based Task Offloading and Resource Allocation for Smart Cities in a Mobile Edge Network
por: Chen, Xing, et al.
Publicado: (2022)

Deep Reinforcement Learning Multi-Agent System for Resource Allocation in Industrial Internet of Things
por: Rosenberger, Julia, et al.
Publicado: (2022)

Deep Reinforcement Learning Based Resource Allocation Strategy in Cloud-Edge Computing System
por: Xu, Jianqiao, et al.
Publicado: (2022)

Deep Reinforcement Learning-Assisted Optimization for Resource Allocation in Downlink OFDMA Cooperative Systems
por: Tefera, Mulugeta Kassaw, et al.
Publicado: (2023)

Self-controlling photonic-on-chip networks with deep reinforcement learning
por: Do, Nguyen, et al.
Publicado: (2021)

Slice Management for Quality of Service Differentiation in Wireless Network Slicing
por: An, Namwon, et al.
Publicado: (2019)

Deep Reinforcement Learning in Action
por: Brown, Brandon
Publicado: (2020)

Deep Reinforcement Learning Hands-On
por: Lapan, Maxim
Publicado: (2020)

Deep Reinforcement Learning with Python
por: Ravichandiran, Sudharsan
Publicado: (2020)

An introduction to deep reinforcement learning
por: François-Lavet, Vincent, et al.
Publicado: (2018)

Grokking Deep Reinforcement Learning
por: Morales, Miguel
Publicado: (2020)

Computed Tomography slice interpolation in the longitudinal direction based on deep learning techniques: To reduce slice thickness or slice increment without dose increase
por: Wu, Shuqiong, et al.
Publicado: (2022)

BeiDou Short-Message Satellite Resource Allocation Algorithm Based on Deep Reinforcement Learning
por: Xia, Kaiwen, et al.
Publicado: (2021)

Deep Reinforcement Learning-Based Resource Allocation for Satellite Internet of Things with Diverse QoS Guarantee
por: Tang, Siqi, et al.
Publicado: (2022)

An Optimization-Based Orchestrator for Resource Access and Operation Management in Sliced 5G Core Networks
por: Hsiao, Chiu-Han, et al.
Publicado: (2021)

Evaluation of transfer learning in deep convolutional neural network models for cardiac short axis slice classification
por: Ho, Namgyu, et al.
Publicado: (2021)

Random Access Using Deep Reinforcement Learning in Dense Mobile Networks
por: Bekele, Yared Zerihun, et al.
Publicado: (2021)

Deep Reinforcement Learning for Edge Caching with Mobility Prediction in Vehicular Networks
por: Choi, Yoonjeong, et al.
Publicado: (2023)

Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey
por: Orr, James, et al.
Publicado: (2023)

Learn to Steer through Deep Reinforcement Learning
por: Wu, Keyu, et al.
Publicado: (2018)

Learning Macromanagement in Starcraft by Deep Reinforcement Learning
por: Huang, Wenzhen, et al.
Publicado: (2021)

Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction
por: Gassenmaier, Sebastian, et al.
Publicado: (2023)

Dynamic Resource Allocation for Network Slicing with Multi-Tenants in 5G Two-Tier Networks
por: Lin, Jia-You, et al.
Publicado: (2023)

Deep Reinforcement Learning for Computation Offloading and Resource Allocation in Unmanned-Aerial-Vehicle Assisted Edge Computing
por: Li, Shuyang, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_podjmaj9257qr5aafqefvbe2gt