DeepCog: Optimizing resource provisioning in network slicing with AI-based capacity forecasting
The dynamic management of network resources is both a critical and challenging task in
upcoming multi-tenant mobile networks, which requires allocating capacity to individual …
upcoming multi-tenant mobile networks, which requires allocating capacity to individual …
AZTEC: Anticipatory capacity allocation for zero-touch network slicing
The combination of network softwarization with network slicing enables the provisioning of
very diverse services over the same network infrastructure. However, it also creates a …
very diverse services over the same network infrastructure. However, it also creates a …
Mobile traffic forecasting for maximizing 5G network slicing resource utilization
V Sciancalepore, K Samdanis… - … -IEEE conference on …, 2017 - ieeexplore.ieee.org
The emerging network slicing paradigm for 5G provides new business opportunities by
enabling multi-tenancy support. At the same time, new technical challenges are introduced …
enabling multi-tenancy support. At the same time, new technical challenges are introduced …
DeepSlice: A deep learning approach towards an efficient and reliable network slicing in 5G networks
Existing cellular communications and the upcoming 5G mobile network requires meeting
high-reliability standards, very low latency, higher capacity, more security, and high-speed …
high-reliability standards, very low latency, higher capacity, more security, and high-speed …
DeepCog: Cognitive network management in sliced 5G networks with deep learning
Network slicing is a new paradigm for future 5G networks where the network infrastructure is
divided into slices devoted to different services and customized to their needs. With this …
divided into slices devoted to different services and customized to their needs. With this …
ADAPTIVE6G: Adaptive resource management for network slicing architectures in current 5G and future 6G systems
A Thantharate, C Beard - Journal of Network and Systems Management, 2023 - Springer
Future intelligent wireless networks demand an adaptive learning approach towards a
shared learning model to allow collaboration between data generated by network elements …
shared learning model to allow collaboration between data generated by network elements …
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 …
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 …
Intelligent resource scheduling for 5G radio access network slicing
It is widely acknowledged that network slicing can tackle the diverse use cases and
connectivity services of the forthcoming next-generation mobile networks (5G). Resource …
connectivity services of the forthcoming next-generation mobile networks (5G). Resource …
Customized slicing for 6G: Enforcing artificial intelligence on resource management
Next generation wireless networks are expected to support diverse vertical industries and
offer countless emerging use cases. To satisfy stringent requirements of diversified services …
offer countless emerging use cases. To satisfy stringent requirements of diversified services …