Deep reinforcement learning-based service-oriented resource allocation in smart grids

L Xi, Y Wang, Y Wang, Z Wang, X Wang, Y Chen - IEEE Access, 2021 - ieeexplore.ieee.org
Resource allocation has a direct and profound impact on the performance of resource-
limited smart grids with diversified services that need to be timely processed. In this paper …

RAN slice strategy based on deep reinforcement learning for smart grid

S Meng, Z Wang, H Ding, S Wu, X Li… - … and IoT Applications …, 2019 - ieeexplore.ieee.org
As one of the important application scenarios of the Green Internet of Things (IoT), the
development of smart grid is an important means to promote the energy system revolution …

Deep reinforcement learning based edge computing network aided resource allocation algorithm for smart grid

Y Chi, Y Zhang, Y Liu, H Zhu, Z Zheng, R Liu… - Ieee …, 2022 - ieeexplore.ieee.org
The dramatic increase in the volume of users and services makes scheduling network
resources for smart grids a key challenge. Network slicing is an important technology to …

Joint optimization of computing offloading and service caching in edge computing-based smart grid

H Zhou, Z Zhang, D Li, Z Su - IEEE Transactions on Cloud …, 2022 - ieeexplore.ieee.org
With the continuous expansion of the power Internet of Things (IoT) and the rapid increase in
the number of Smart Devices (SDs), the data generated by SDs has exponentially …

Resource allocation based on deep reinforcement learning in IoT edge computing

X Xiong, K Zheng, L Lei, L Hou - IEEE Journal on Selected …, 2020 - ieeexplore.ieee.org
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 …

Efficient task offloading and resource allocation for edge computing-based smart grid networks

C Yang, X Chen, Y Liu, W Zhong… - ICC 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
By providing computation and storage resources at the edge of the wireless access
networks, edge computing (EC) has been regarded as a provisioning solution to enable the …

Network Resource Allocation Algorithm using Reinforcement Learning Policy-based Network in a Smart Grid Scenario

Z Zheng, Y Han, Y Chi, F Yuan, W Cui, H Zhu, Y Zhang… - Electronics, 2023 - mdpi.com
The exponential growth in user numbers has resulted in an overwhelming surge in data that
the smart grid must process. To tackle this challenge, edge computing emerges as a vital …

Slice allocation of 5G network for smart grid with deep reinforcement learning ACKTR

L Zhong, J Hu, H Shen, C Xu… - 2022 7th International …, 2022 - ieeexplore.ieee.org
Smart grid is one of the representative applications for 5G network. In this scenario, different
business types of smart grid have diverse requirements in service quality, isolation level …

Attention cooperative task offloading and service caching in edge computing

Z Yao, Y Li, S Xia, G Wu - GLOBECOM 2022-2022 IEEE Global …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC) enables various services to be cached in close proximity to
the user equipments (UEs), thereby reducing the computing delay of many emerging …

Deep reinforcement learning based approach for online service placement and computation resource allocation in edge computing

T Liu, S Ni, X Li, Y Zhu, L Kong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Due to the urgent emergence of computation-intensive intelligent applications on end
devices, edge computing has been put forward as an extension of cloud computing, to …