Priority-based dynamic resource allocation scheme in network slicing
In the network slicing environment, if insufficient resource is allocated to a resource-hungry
slice (eg, ultrareliable low latency communication (URLLC)), its quality of service (QoS) can …
slice (eg, ultrareliable low latency communication (URLLC)), its quality of service (QoS) can …
ECP: Error-Aware, Cost-Effective and Proactive Network Slicing Framework
AE Aboeleneen, AA Abdellatif… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Recent advancements in Software Defined Networks (SDN), Open Radio Access Network
(O-RAN), and 5G technology have significantly expanded the capabilities of wireless …
(O-RAN), and 5G technology have significantly expanded the capabilities of wireless …
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 …
Time-Varying Real-Time Online Multi-Resource Allocation for Scaling the Slices and VNF Isolation
A Majidi, N Jahanbakhsh… - IEEE INFOCOM 2023-IEEE …, 2023 - ieeexplore.ieee.org
The infrastructure of mobile networks in 5G will offer various services in the form of network
slices that can be deployed and implemented in a highly customizable manner. A real …
slices that can be deployed and implemented in a highly customizable manner. A real …
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 …
Joint Demand Forecasting and Network Slice Pricing for Profit Maximization in Network Slicing
As a key technology of next-generation networks, network slicing enables networks to
flexibly and efficiently fulfill the heterogeneous requirements of various services. In the slice …
flexibly and efficiently fulfill the heterogeneous requirements of various services. In the slice …
Two-tier resource allocation in dynamic network slicing paradigm with deep reinforcement learning
Network slicing is treated as a key technology of the rapidly developing 5G system.
Nevertheless, the environment of the users is extremely complex, leading to a great …
Nevertheless, the environment of the users is extremely complex, leading to a great …
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 …
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 …