… system necessitates the ability to federate learning in order to meet the changing service …
on 3D communication platforms that can enable almost instantaneous distributed edge cloud …

… Intelligence)-based techniques such as deep learning meet … for the edge networks where
UE nodes are evolving to be … we adopt a computing scenario in multi-cloud settings which is …

… Furthermore, the integration of artificial intelligence (AI) and machine learning within cloud
… a comprehensive understanding of the evolution of cloud computing, its potential future …

… paradigm that aims to push cloud resources closer to the end user … Thirdly, edge networks
evolve with dynamic user … network while meeting the storage constraints at the edge. ML …

… (IIoT), edge and cloud computing, machine learning, artificial … communication layers to
meet the monitoring and control … learning evolution at the twins at both the cloud and edge …

… Compared to the cloud, the edge can broaden the computation … The evolution and development
of DRL are intensely … the target while meeting the data computation and communication …

… Nowadays, various machine learning and deep learning … at the local edge devices or the
collaboration of edge-cloud serv… Along with the evolution and importance of 6G communication, …

… , cloud and knowledge by combining digital twin and with deep learning approaches, … ,
distributed joint simulation technology and the idea of co-evolution of the “terminal-edge-cloud”. …

… objects created in the edge cloud constitute an important … is proposed based on deep
reinforcement learning (DRL) in DITEN … 7 depicts the the task failure rate changing with the …

… edge computing and distributed machine learning (ML), edgebased ML called federated
learning has emerged to overcome the shortcomings of cloud-… is always changing very fast. For …