Reinforcement learning based resource management for network slicing
Network slicing to create multiple virtual networks, called network slice, is a promising
technology to enable networking resource sharing among multiple tenants for the 5th …
technology to enable networking resource sharing among multiple tenants for the 5th …
Deep reinforcement learning for resource management on network slicing: A survey
JA Hurtado Sánchez, K Casilimas… - Sensors, 2022 - mdpi.com
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 …
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …
A sub-action aided deep reinforcement learning framework for latency-sensitive network slicing
Network slicing is a core technique of fifth-generation (5G) systems and beyond. To
maximize the number of accepted network slices with limited hardware resources, service …
maximize the number of accepted network slices with limited hardware resources, service …
Machine learning for network slicing resource management: A comprehensive survey
B Han, HD Schotten - arXiv preprint arXiv:2001.07974, 2020 - arxiv.org
The emerging technology of multi-tenancy network slicing is considered as an essential
feature of 5G cellular networks. It provides network slices as a new type of public cloud …
feature of 5G cellular networks. It provides network slices as a new type of public cloud …
DeepSlicing: Deep reinforcement learning assisted resource allocation for network slicing
Network slicing enables multiple virtual networks run on the same physical infrastructure to
support various use cases in 5G and beyond. These use cases, however, have very diverse …
support various use cases in 5G and beyond. These use cases, however, have very diverse …
Learning-based dynamic resource provisioning for network slicing with ensured end-to-end performance bound
To accommodate different sets of network functions with different quality-of-service
requirements for different types of applications in 5G networks, network slicing, which …
requirements for different types of applications in 5G networks, network slicing, which …
Machine learning-based QoS and traffic-aware prediction-assisted dynamic network slicing
N Kumar, A Ahmad - International Journal of …, 2022 - inderscienceonline.com
Over the last few years, network slicing has been presented as one of the key ingredients in
5G for efficiently specifying network services as per the heterogeneous quality and …
5G for efficiently specifying network services as per the heterogeneous quality and …
Data-driven dynamic resource scheduling for network slicing: A deep reinforcement learning approach
Network slicing is designed to support a variety of emerging applications with diverse
performance and flexibility requirements, by dividing the physical network into multiple …
performance and flexibility requirements, by dividing the physical network into multiple …
Deep reinforcement learning with discrete normalized advantage functions for resource management in network slicing
Network slicing promises to provision diversified services with distinct requirements in one
infrastructure. Deep reinforcement learning (eg, deep Q-learning, DQL) is assumed to be an …
infrastructure. Deep reinforcement learning (eg, deep Q-learning, DQL) is assumed to be an …
Optimizing network slice dimensioning via resource pricing
Network slicing has been viewed as a key enabler for the next-generation software-defined
and cloud-based network (eg, 5G and beyond) to accommodate diverse services in a …
and cloud-based network (eg, 5G and beyond) to accommodate diverse services in a …
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