Green resource allocation based on deep reinforcement learning in content-centric IoT
In the era of information, the green services of content-centric IoT are expected to offer users
the better satisfaction of Quality of Experience (QoE) than that in a conventional IoT …
the better satisfaction of Quality of Experience (QoE) than that in a conventional IoT …
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 …
Joint optimization of caching, computing, and radio resources for fog-enabled IoT using natural actor–critic deep reinforcement learning
The cloud-based Internet of Things (IoT) develops rapidly but suffer from large latency and
backhaul bandwidth requirement, the technology of fog computing and caching has …
backhaul bandwidth requirement, the technology of fog computing and caching has …
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 …
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 …
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 …
Optimal resource allocation using reinforcement learning for IoT content-centric services
The exponential growing rate of the networking technologies has led to a dramatical large
scope of the connected computing environment. Internet-of-Things (IoT) is considered an …
scope of the connected computing environment. Internet-of-Things (IoT) is considered an …
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 …
Dynamic task allocation and service migration in edge-cloud iot system based on deep reinforcement learning
Edge computing (EC) extends the ability of cloud computing to the network edge to support
diverse resource-sensitive and performance-sensitive IoT applications. However, due to the …
diverse resource-sensitive and performance-sensitive IoT applications. However, due to the …
Joint admission control and resource allocation in edge computing for internet of things
The IoT is a novel platform for making objects more intelligent by connecting to the Internet.
However, mass connections, big data processing, and huge power consumption restrict the …
However, mass connections, big data processing, and huge power consumption restrict the …
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