Edge computing smart grid resource scheduling algorithm based on reinforcement learning
A smart grid is a power network capable of intelligent management and optimization.Network virtualization technology can effectively improve the resource utilization and reliability of smart grids and meet the differentiated needs of different users.In the case of limited resources, traditional virt...
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Format: | Article |
Language: | zho |
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Beijing Xintong Media Co., Ltd
2024-01-01
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Series: | Dianxin kexue |
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Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024005/ |
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author | Jinghang YU Yichen ZHAO Hu SONG |
author_facet | Jinghang YU Yichen ZHAO Hu SONG |
author_sort | Jinghang YU |
collection | DOAJ |
description | A smart grid is a power network capable of intelligent management and optimization.Network virtualization technology can effectively improve the resource utilization and reliability of smart grids and meet the differentiated needs of different users.In the case of limited resources, traditional virtual network embedding algorithms cannot dynamically adjust the allocation and mapping of virtual resources according to the resource usage and user needs of the power system.To solve this problem, edge computing and virtualization technology was combined and a virtual network resource scheduling algorithm based on reinforcement learning was introduced.The simulation results show that the proposed virtual resource scheduling algorithm is better than the other three scheduling algorithms in improving power grid reliability and resource utilization. |
format | Article |
id | doaj-art-cb0d37b16d9e4edaab876870db610702 |
institution | Kabale University |
issn | 1000-0801 |
language | zho |
publishDate | 2024-01-01 |
publisher | Beijing Xintong Media Co., Ltd |
record_format | Article |
series | Dianxin kexue |
spelling | doaj-art-cb0d37b16d9e4edaab876870db6107022025-01-15T02:57:33ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012024-01-014011512259557220Edge computing smart grid resource scheduling algorithm based on reinforcement learningJinghang YUYichen ZHAOHu SONGA smart grid is a power network capable of intelligent management and optimization.Network virtualization technology can effectively improve the resource utilization and reliability of smart grids and meet the differentiated needs of different users.In the case of limited resources, traditional virtual network embedding algorithms cannot dynamically adjust the allocation and mapping of virtual resources according to the resource usage and user needs of the power system.To solve this problem, edge computing and virtualization technology was combined and a virtual network resource scheduling algorithm based on reinforcement learning was introduced.The simulation results show that the proposed virtual resource scheduling algorithm is better than the other three scheduling algorithms in improving power grid reliability and resource utilization.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024005/smart gridedge computingvirtual network embeddingresource scheduling |
spellingShingle | Jinghang YU Yichen ZHAO Hu SONG Edge computing smart grid resource scheduling algorithm based on reinforcement learning Dianxin kexue smart grid edge computing virtual network embedding resource scheduling |
title | Edge computing smart grid resource scheduling algorithm based on reinforcement learning |
title_full | Edge computing smart grid resource scheduling algorithm based on reinforcement learning |
title_fullStr | Edge computing smart grid resource scheduling algorithm based on reinforcement learning |
title_full_unstemmed | Edge computing smart grid resource scheduling algorithm based on reinforcement learning |
title_short | Edge computing smart grid resource scheduling algorithm based on reinforcement learning |
title_sort | edge computing smart grid resource scheduling algorithm based on reinforcement learning |
topic | smart grid edge computing virtual network embedding resource scheduling |
url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024005/ |
work_keys_str_mv | AT jinghangyu edgecomputingsmartgridresourceschedulingalgorithmbasedonreinforcementlearning AT yichenzhao edgecomputingsmartgridresourceschedulingalgorithmbasedonreinforcementlearning AT husong edgecomputingsmartgridresourceschedulingalgorithmbasedonreinforcementlearning |