… We briefly introduce 5G network slicing and deep learning concepts in Section II, some
background work details are in Section III, we explain our DeepSlice model in Section IV and in …

… with an enormous number of mobile phones due to these applications. This … the network
slicing performance. This work aims to design an efficient network slicing using a hybrid learning …

… To tackle it, we propose a novel deep learning approach using the dueling neural network …
We consider a general network slicing model with three major parties: (i) the network provider, …

… learning based reconfigurable wireless network … network requests, perform load balancing,
optimum utilization of resources, and restricting network slice failure a hybrid deep learning …

… situations and network traffic groups that are operating on the same networks using a network
slicing architecture [4]. Because of network slicing, it is possible to build many 5G networks …

… We present a fast-learning DRL model that can dynamically optimize the network slice
configuration in Wi-Fi networks. Our network slices require each a different network configuration. …

… Deep Federated Reinforcement Learning-based Network Slicing approach, to provide slice’s
… a network slicing architecture based on SDN and NFV for IIoT 4.0 to meet multitude slice …

… (5G) communication system, network slicing can share the underlying … network slicing
resource allocation algorithm based on Deep Q-Networks (DQN), which is suitable for multi-slice …

… opportunity for the management of network slicing resources. Leveraging the knowledge …
a novel Machine Learning-based scheme for dynamic resource scheduling for networks slicing, …

… network into multiple slices supporting independent services. In beyond 5G (B5G) systems,
the main goal of network slicing … a deep reinforcement learning (DRL)-based network slicing …