Real-time network slicing with uncertain demand: A deep learning approach
Practical and efficient network slicing often faces real-time dynamics of network resources
and uncertain customer demands. This work provides an optimal and fast resource slicing …
and uncertain customer demands. This work provides an optimal and fast resource slicing …
Optimal and fast real-time resource slicing with deep dueling neural networks
Effective network slicing requires an infrastructure/network provider to deal with the
uncertain demands and real-time dynamics of the network resource requests. Another …
uncertain demands and real-time dynamics of the network resource requests. Another …
Resource allocation method for network slicing using constrained reinforcement learning
With the proliferation of mobile networks, we face strong diversification of services,
demanding the network to be more flexible. To satisfy this dire need, network slicing is …
demanding the network to be more flexible. To satisfy this dire need, network slicing is …
A constrained reinforcement learning based approach for network slicing
With the proliferation of mobile networks, we face strong diversification of services,
demanding the current network to embed more flexibility. To satisfy this daring need …
demanding the current network to embed more flexibility. To satisfy this daring need …
CLARA: A constrained reinforcement learning based resource allocation framework for network slicing
As mobile networks proliferate, we are experiencing a strong diversification of services,
which requires greater flexibility from the existing network. Network slicing is proposed as a …
which requires greater flexibility from the existing network. Network slicing is proposed as a …
GAN-based deep distributional reinforcement learning for resource management in network slicing
Network slicing is a key technology in 5G communications system, which aims to
dynamically and efficiently allocate resources for diversified services with distinct …
dynamically and efficiently allocate resources for diversified services with distinct …
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 …
AI-enabled automated and closed-loop optimization algorithms for delay-aware network
Network slicing is one of the core techniques of the current 5G networks. To accommodate
as many network slices as possible with limited hardware resources, service providers need …
as many network slices as possible with limited hardware resources, service providers need …
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 …
Digital twin-enhanced deep reinforcement learning for resource management in networks slicing
Network slicing-based communication systems can dynamically and efficiently allocate
resources for diversified services. However, due to the limitation of the network interface on …
resources for diversified services. However, due to the limitation of the network interface on …
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- real time network
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