… , the current cloud computing service architecture hinders the … that the cloud would have
difficulty meeting since it may be … accurately model rapidly changing edge network environments …

… cloud computing model may nevertheless encounter many problems in independently tackling
the massive data generated by IoT and meeting … Other algorithms such as evolutionary …

… cloud computing. The trend of deploying machine learning (ML) at the network edge to enhance
… low latency within a few milliseconds that can hardly be met by the existing cloud model. …

… 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 …

… with human-control, and empower the networks to self-control, to adapt, and to heal themselves
with the changing user, traffic … A survey on ML techniques for edge and cloud platforms …

… elastic services has shown superiorities to meet the computing needs dynamically. Without
an … We discuss the evolution of RL and DRL frameworks in this section, in order to provide a …

… techniques in the cloud integrated computing paradigms is in the trend to meet several QoS
… Cloud computing is evolving beyond the commercial and consumer markets to include …

… limitations of the edge servers, with respect to a cloud, and … reliability need to evolve from
classical communication-related … (1),(5),(6)) to meet the desired latency constraint. In this work, …

… To this end, we propose a multi-agent reinforcement learning algorithm to decide whether …
“Machine learning meets computation and communication control in evolving edge and cloud: …

… Kato, “Machine learning meets computation and communication control in evolving edge
and cloud: Challenges and future perspective,” IEEE Commun. Surveys Tuts., vol. 22, no. …