Deep reinforcement learning for edge computing and resource allocation in 5G beyond
Y Dai, D Xu, K Zhang, Y Lu… - 2019 IEEE 19th …, 2019 - ieeexplore.ieee.org
By extending computation capacity to the edge of wireless networks, edge computing has
the potential to enable computation-intensive and delay-sensitive applications in 5G and …
the potential to enable computation-intensive and delay-sensitive applications in 5G and …
Edge intelligence for energy-efficient computation offloading and resource allocation in 5G beyond
Y Dai, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
5G beyond is an end-edge-cloud orchestrated network that can exploit heterogeneous
capabilities of the end devices, edge servers, and the cloud and thus has the potential to …
capabilities of the end devices, edge servers, and the cloud and thus has the potential to …
Deep reinforcement learning based computation offloading and resource allocation for MEC
Mobile edge computing (MEC) has the potential to enable computation-intensive
applications in 5G networks. MEC can extend the computational capacity at the edge of …
applications in 5G networks. MEC can extend the computational capacity at the edge of …
Joint optimization of task offloading and resource allocation via deep reinforcement learning for augmented reality in mobile edge network
X Chen, G Liu - 2020 IEEE International Conference on Edge …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) has been recognized as emerging techniques in 5G to
provide powerful computing capabilities for the Ultra Reliable Low Latency Communication …
provide powerful computing capabilities for the Ultra Reliable Low Latency Communication …
Joint computation offloading and resource configuration in ultra-dense edge computing networks: A deep reinforcement learning solution
The prompt development of wireless communication network and emerging technologies
such as Internet of Things (IoT) and 5G have increased the number of various mobile …
such as Internet of Things (IoT) and 5G have increased the number of various mobile …
Intelligent offloading for multi-access edge computing: A new actor-critic approach
KH Liu, W Liao - ICC 2020-2020 IEEE International Conference …, 2020 - ieeexplore.ieee.org
Multi-access Edge Computing (MEC) is promising to handle computation-intensive and
latency-sensitive applications for 5G and beyond. Users can benefit from task offloading via …
latency-sensitive applications for 5G and beyond. Users can benefit from task offloading via …
Computation offloading in beyond 5G networks: A distributed learning framework and applications
Facing the trend of merging wireless communications and multi-access edge computing
(MEC), this article studies computation offloading in beyond fifth generation networks. To …
(MEC), this article studies computation offloading in beyond fifth generation networks. To …
Deep reinforcement learning aided task partitioning and computation offloading in mobile edge computing
With the wave of the Internet of Things (IoT), a vast number of IoT devices are connected to
wireless networks. To better support the Quality of Service of IoT devices with constrained …
wireless networks. To better support the Quality of Service of IoT devices with constrained …
Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …
architecture, which can empower user equipments (UEs) with computation and energy …
Multi-user multi-channel computation offloading and resource allocation for mobile edge computing
We study the problem of computation offloading and resourceallocation in multi-user multi-
channel mobile edge computing (MEC) systems. Each user equipment (UE) in the system …
channel mobile edge computing (MEC) systems. Each user equipment (UE) in the system …
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