[HTML][HTML] A reinforcement-learning-based distributed resource selection algorithm for massive IoT
J Ma, S Hasegawa, SJ Kim, M Hasegawa - Applied Sciences, 2019 - mdpi.com
Massive IoT including the large number of resource-constrained IoT devices has gained
great attention. IoT devices generate enormous traffic, which causes network congestion. To …
great attention. IoT devices generate enormous traffic, which causes network congestion. To …
Performance evaluation of reinforcement learning based distributed channel selection algorithm in massive IoT networks
In recent years, the demand for new applications using various Internet of Things (IoT)
devices has led to an increase in the number of devices connected to wireless networks …
devices has led to an increase in the number of devices connected to wireless networks …
A machine-learning-based channel assignment algorithm for IoT
J Ma, T Nagatsuma, SJ Kim… - … conference on artificial …, 2019 - ieeexplore.ieee.org
Multi-channel technique benefits IoT network by support parallel transmission and reduce
interference. However, the extra overhead posed by the multi-channel usage coordination …
interference. However, the extra overhead posed by the multi-channel usage coordination …
An intelligent traffic load prediction-based adaptive channel assignment algorithm in SDN-IoT: A deep learning approach
Due to the fast increase of sensing data and quick response requirement in the Internet of
Things (IoT) delivery network, the high speed transmission has emerged as an important …
Things (IoT) delivery network, the high speed transmission has emerged as an important …
A new block-based reinforcement learning approach for distributed resource allocation in clustered IoT networks
Resource allocation and spectrum management are two major challenges in the massive
scale deployment of Internet of Things (IoT) and Machine-to-Machine (M2M) communication …
scale deployment of Internet of Things (IoT) and Machine-to-Machine (M2M) communication …
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 …
On a novel deep-learning-based intelligent partially overlapping channel assignment in SDN-IoT
Recently, SDN has emerged as a promising technology to cost-effectively provide the scale
and flexibility necessary for IoT services. In this article, we consider the wireless SDN for IoT …
and flexibility necessary for IoT services. In this article, we consider the wireless SDN for IoT …
Performance evaluation of machine learning based channel selection algorithm implemented on IoT sensor devices in coexisting IoT networks
The number of IoT devices may dramatically increase in the near future. Numerous IoT
devices may generate enormous traffic, which causes network congestions and packet …
devices may generate enormous traffic, which causes network congestions and packet …
Resource-Constraint Network Selection for IoT under the Unknown and Dynamic Heterogeneous Wireless Environment
Z Xu, Z Zhang, S Wang, Y Yan… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
We investigate the problem of network selection for the Internet of Things (IoT) to maximize
the Quality of Experience (QoE) in a heterogeneous wireless environment. Different from the …
the Quality of Experience (QoE) in a heterogeneous wireless environment. Different from the …
Edge-based federated deep reinforcement learning for IoT traffic management
A Jarwan, M Ibnkahla - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
The wide adoption of large-scale Internet of Things (IoT) systems has led to an
unprecedented increase in backhaul (BH) traffic congestion, making it critical to optimize …
unprecedented increase in backhaul (BH) traffic congestion, making it critical to optimize …