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Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
The rapid production of mobile devices along with the wireless applications boom is continuing to evolve daily. This motivates the exploitation of wireless spectrum using multiple Radio Access Technologies (multi-RAT) and ...
Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems and speech processing applications to robotics ...
Dynamic Network Slicing and Resource Allocation for 5G-and-Beyond Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
5G networks are designed not only to transport data, but also to process them while supporting a vast number of services with different key Performance Indicators (KPIs). Network virtualization has emerged to enable this ...
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
(
IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...
RLENS: RL-based Energy-Efficient Network Selection Framework for IoMT
(
IEEE
, 2022 , Conference Paper)
With the emergence of smart health (s-health) applications and services, several requirements for quality have arisen to foresee and react instantaneously to emergency circumstances. Such requirements demand fast-acting ...
RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning
(2022 , Conference Paper)
The extremely heavy global reliance on IoT devices is causing enormous amounts of data to be gathered and shared in IoT networks. Such data need to efficiently be used in training and deploying of powerful artificially ...