Resource allocation based on deep reinforcement learning in IoT edge computing
By leveraging mobile edge computing (MEC), a huge amount of data generated by Internet
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …
iRAF: A deep reinforcement learning approach for collaborative mobile edge computing IoT networks
Recently, as the development of artificial intelligence (AI), data-driven AI methods have
shown amazing performance in solving complex problems to support the Internet of Things …
shown amazing performance in solving complex problems to support the Internet of Things …
Deep reinforcement learning-based task scheduling in iot edge computing
Edge computing (EC) has recently emerged as a promising paradigm that supports resource-
hungry Internet of Things (IoT) applications with low latency services at the network edge …
hungry Internet of Things (IoT) applications with low latency services at the network edge …
Multiuser resource control with deep reinforcement learning in IoT edge computing
By leveraging the concept of mobile edge computing (MEC), massive amount of data
generated by a large number of Internet of Things (IoT) devices could be offloaded to MEC …
generated by a large number of Internet of Things (IoT) devices could be offloaded to MEC …
Deep reinforcement learning based mobile edge computing for intelligent Internet of Things
R Zhao, X Wang, J Xia, L Fan - Physical Communication, 2020 - Elsevier
In this paper, we investigate mobile edge computing (MEC) networks for intelligent internet
of things (IoT), where multiple users have some computational tasks assisted by multiple …
of things (IoT), where multiple users have some computational tasks assisted by multiple …
Resource allocation with edge computing in IoT networks via machine learning
In this article, we investigate resource allocation with edge computing in Internet-of-Things
(IoT) networks via machine learning approaches. Edge computing is playing a promising …
(IoT) networks via machine learning approaches. Edge computing is playing a promising …
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 …
Task-driven resource assignment in mobile edge computing exploiting evolutionary computation
The IoT network allows IoT devices to communicate with other devices, applications, and
services by exploiting existing network infrastructure. Recently, a promising paradigm, MEC …
services by exploiting existing network infrastructure. Recently, a promising paradigm, MEC …
Resource allocation for edge computing in IoT networks via reinforcement learning
In this paper, we consider resource allocation for edge computing in internet of things (IoT)
networks. Specifically, each end device is considered as an agent, which makes its …
networks. Specifically, each end device is considered as an agent, which makes its …
Reinforcement-learning-and belief-learning-based double auction mechanism for edge computing resource allocation
In recent years, we have witnessed the compelling application of the Internet of Things (IoT)
in our daily life, ranging from daily living to industrial production. On account of the …
in our daily life, ranging from daily living to industrial production. On account of the …
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