… 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 …

… 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 …

… 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 …

… 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 …

… principle of network slicing, state the challenges faced by the RAN slicing, and then discuss
the importance of applying deep reinforcement learning (DRL) in the context of RAN slicing. …

… security threats to a network slice [7]. A DDoS attack in the network slicing scenario is an attack
… A DDoS attack against a slice in a 5G network, if successfully deployed, may impact other …

… operator (MNO) can allocate network resources dynamically and flexibly to each logical
network slice … of resource allocation with machine learning methods in vehicular network slicing. …

… based on network slicing. Network slicing is an effective solution to satisfy the requirements
of various use cases of wireless networks in general and vehicular networks in particular [17]…