Deep federated Q-learning-based network slicing for industrial IoT
Fifth generation and beyond networks are envisioned to support multi industrial Internet of
Things (IIoT) applications with a diverse quality-of-service (QoS) requirements. Network …
Things (IIoT) applications with a diverse quality-of-service (QoS) requirements. Network …
Transfer reinforcement learning aided distributed network slicing optimization in industrial IoT
With the growth of the number of Internet of Things (IoT) devices and the emergence of new
applications, satisfying distinct QoS in the same physical network becomes more …
applications, satisfying distinct QoS in the same physical network becomes more …
Digital twin assisted resource allocation for network slicing in industry 4.0 and beyond using distributed deep reinforcement learning
L Tang, Y Du, Q Liu, J Li, S Li… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Personalization is one of the primary emerging trends in Industry 4.0 and Beyond. Highly
personalized services will present a significant challenge to the existing algorithms for …
personalized services will present a significant challenge to the existing algorithms for …
Edgeslice: Slicing wireless edge computing network with decentralized deep reinforcement learning
5G and edge computing will serve various emerging use cases that have diverse
requirements of multiple resources, eg, radio, transportation, and computing. Network slicing …
requirements of multiple resources, eg, radio, transportation, and computing. Network slicing …
QoS guaranteed network slicing orchestration for Internet of Vehicles
Y Cui, X Huang, P He, D Wu… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
To support the diversified Quality of Service (QoS) requirements of application scenarios,
network slicing has been introduced in the mobile cellular network. It allows mobile cellular …
network slicing has been introduced in the mobile cellular network. It allows mobile cellular …
A survey of intelligent network slicing management for industrial IoT: Integrated approaches for smart transportation, smart energy, and smart factory
Network slicing has been widely agreed as a promising technique to accommodate diverse
services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and …
services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and …
Zero-touch AI-driven distributed management for energy-efficient 6G massive network slicing
Sixth-generation (6G) systems are expected to inaugurate the era of massive and extremely
heterogeneous network slicing, where tenancy would be extended to the final consumer …
heterogeneous network slicing, where tenancy would be extended to the final consumer …
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 …
Multi-agent reinforcement learning-based resource management for end-to-end network slicing
To meet the explosive growth of mobile traffic, the 5G network is designed to be flexible and
support multi-access edge computing (MEC), thereby improving the end-to-end quality of …
support multi-access edge computing (MEC), thereby improving the end-to-end quality of …
On the specialization of fdrl agents for scalable and distributed 6g ran slicing orchestration
Network slicing enables multiple virtual networks to be instantiated and customized to meet
heterogeneous use case requirements over 5G and beyond network deployments …
heterogeneous use case requirements over 5G and beyond network deployments …
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