Intelligent-driven green resource allocation for industrial Internet of Things in 5G heterogeneous networks
P Yu, M Yang, A Xiong, Y Ding, W Li… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) is one of the important applications under the 5G
massive machine type of communication (mMTC) scenario. To ensure the high reliability of …
massive machine type of communication (mMTC) scenario. To ensure the high reliability of …
Resource allocation for multi-UAV assisted IoT networks: A deep reinforcement learning approach
YY Munaye, RT Juang, HP Lin… - … on Pervasive Artificial …, 2020 - ieeexplore.ieee.org
The wireless communication system for the massively heterogeneous Internet of Things
(IoT) network hinders the allocation of resources. For this study, an unmanned aerial vehicle …
(IoT) network hinders the allocation of resources. For this study, an unmanned aerial vehicle …
Multi-agent reinforcement learning for resource allocation in IoT networks with edge computing
To support popular Internet of Things (IoT) applications such as virtual reality and mobile
games, edge computing provides a front-end distributed computing archetype of centralized …
games, edge computing provides a front-end distributed computing archetype of centralized …
Edge based priority-aware dynamic resource allocation for Internet of Things networks
The exponential growth of the edge-based Internet-of-Things (IoT) services and its
ecosystems has recently led to a new type of communication network, the Low Power Wide …
ecosystems has recently led to a new type of communication network, the Low Power Wide …
Deep reinforcement learning based resource management in UAV-assisted IoT networks
YY Munaye, RT Juang, HP Lin, GB Tarekegn, DB Lin - Applied Sciences, 2021 - mdpi.com
The resource management in wireless networks with massive Internet of Things (IoT) users
is one of the most crucial issues for the advancement of fifth-generation networks. The main …
is one of the most crucial issues for the advancement of fifth-generation networks. The main …
Learning-based resource management for low-power and lossy IoT networks
A Musaddiq, R Ali, SW Kim… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Internet of Things (IoT) networks are key to the realization of modern industries and
societies. A key application of IoT is in smart-grid communications. Smart-grid networks are …
societies. A key application of IoT is in smart-grid communications. Smart-grid networks are …
DeepEdge: A new QoE-based resource allocation framework using deep reinforcement learning for future heterogeneous edge-IoT applications
Edge computing is emerging to empower the future of Internet of Things (IoT) applications.
However, due to heterogeneity of applications, it is a significant challenge for the edge cloud …
However, due to heterogeneity of applications, it is a significant challenge for the edge cloud …
Hypergraph based resource-efficient collaborative reinforcement learning for B5G massive IoT
F Yang, C Yang, J Huang, K Yu, S Garg… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Beyond 5G (B5G) networks rapidly growing to connect billions of Internet of Things (IoT)
devices and the dense deployment of IoT devices leads the large-scale network conflict and …
devices and the dense deployment of IoT devices leads the large-scale network conflict and …
Multiagent reinforcement learning meets random access in massive cellular internet of things
Internet of Things (IoT) has attracted considerable attention in recent years due to its
potential of interconnecting a large number of heterogeneous wireless devices. However, it …
potential of interconnecting a large number of heterogeneous wireless devices. However, it …
Throughput-aware cooperative reinforcement learning for adaptive resource allocation in device-to-device communication
Device-to-device (D2D) communication is an essential feature for the future cellular
networks as it increases spectrum efficiency by reusing resources between cellular and D2D …
networks as it increases spectrum efficiency by reusing resources between cellular and D2D …