… balancing in an IoT edge system meets two main challenges: … of the DRL model by adaptively
changing the clustering pattern of … systems, deep learning, cloud computing, and process …

… Evolving Domain Adaptation Network (EDAN). In case studies, it is verified that the proposed
transfer deep reinforcement learning … for edge computing to meet the computational latency …

… and reinforcement learning technique to realize cloudedge-… according to the changing
computing environment without … users, centralized cloud processing still cannot meet the real-…

… sources, the constant evolution of energy storage technologies, … the evolution of cloud
computing technologies and machine … to meet the highly flexible and distributed computing needs …

… [12] employed a novel deep reinforcement learning (DRL) … of the IoT with AI aided by
edge computing and the cloud. … services for the explosive evolution of information communication …

… -access edge computing was extracted from cloud technology … Based on the advanced
machine learning analysis, the smart … costs of operation, meeting changing consumer demands, …

… demand to meet some of the changing requirements is needed. … and edge, or fog/edge, to
encompass all non-cloud localities. … Machine learning is not a new concept but it has recently …

… privacy computing and edge computing, and effectively meets … leveraging cloud computing
and deep reinforcement learning … Looking ahead, the continued evolution of cloud computing …

… issues of computation offloading evolve into the main obstacles. In this … cloud-edge-end
collaboration PIoT (BASE-PIoT) architecture to ensure data security and intelligent computation …

… combination of deep learning and reinforcement learning (RL… Cloud scheduling, we provide
a comprehensive review for DRL-based methods in resource scheduling of Cloud computing…