Deep reinforcement learning for Internet of Things: A comprehensive survey
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …
communication, computing, caching and control (4Cs) problems. The recent advances in …
The applicability of reinforcement learning methods in the development of industry 4.0 applications
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …
problems. Our article gives a systematic overview of major types of RL methods, their …
Resource-ability assisted service function chain embedding and scheduling for 6G networks with virtualization
While 5G is being deployed all around the world, the industry and academia start the
investigation of 6G. Network function virtualization (NFV) is seen as the key enabler towards …
investigation of 6G. Network function virtualization (NFV) is seen as the key enabler towards …
Age of information aware VNF scheduling in industrial IoT using deep reinforcement learning
In delay-sensitive industrial Internet of Things (IIoT) applications, the age of information (AoI)
is employed to characterize the freshness of information. Meanwhile, the emerging network …
is employed to characterize the freshness of information. Meanwhile, the emerging network …
Dynamic service function chain orchestration for NFV/MEC-enabled IoT networks: A deep reinforcement learning approach
Y Liu, H Lu, X Li, Y Zhang, L ** for industrial IoT using deep reinforcement learning
S Xu, Y Li, S Guo, C Lei, D Liu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The industrial Internet of Things (IIoT) and 5G have been served as the key elements to
support the reliable and efficient operation of Industry 4.0. By integrating burgeoning …
support the reliable and efficient operation of Industry 4.0. By integrating burgeoning …