MH Abidi, H Alkhalefah, K Moiduddin, M Alazab… - Computer Standards & …, 2021 - Elsevier
… with an enormous number of mobile phones due to these applications. This … the network slicing performance. This work aims to design an efficient networkslicing using a hybrid learning …
… To tackle it, we propose a novel deep learningapproach using the dueling neural network … We consider a general networkslicing model with three major parties: (i) the network provider, …
… learning based reconfigurable wirelessnetwork … network requests, perform load balancing, optimum utilization of resources, and restricting networkslice failure a hybrid deep learning …
R Singh, A Mehbodniya, JL Webber… - Wireless …, 2022 - Wiley Online Library
… situations and network traffic groups that are operating on the same networks using a network slicing architecture [4]. Because of networkslicing, it is possible to build many 5G networks …
S De Bast, R Torrea-Duran… - … -IEEE Conference on …, 2019 - ieeexplore.ieee.org
… We present a fast-learning DRL model that can dynamically optimize the networkslice configuration in Wi-Fi networks. Our network slices require each a different network configuration. …
… Deep Federated Reinforcement Learning-based NetworkSlicing approach, to provide slice’s … a networkslicing architecture based on SDN and NFV for IIoT 4.0 to meet multitude slice …
T Li, X Zhu, X Liu - IEEE Access, 2020 - ieeexplore.ieee.org
… (5G) communication system, networkslicing can share the underlying … networkslicing resource allocation algorithm based on Deep Q-Networks (DQN), which is suitable for multi-slice …
… opportunity for the management of networkslicing resources. Leveraging the knowledge … a novel Machine Learning-based scheme for dynamic resource scheduling for networksslicing, …
… network into multiple slices supporting independent services. In beyond 5G (B5G) systems, the main goal of networkslicing … a deep reinforcement learning (DRL)-based networkslicing …