Digital Twin-Empowered Communication Network Resource Management for Low-Carbon Smart Park

被引:3
|
作者
Su, Xiaoyu [1 ]
Jia, Zehan [1 ]
Zhou, Zhenyu [1 ]
Gan, Zhong [2 ]
Wang, Xiaoyan [3 ]
Munitaz, Shahid [4 ]
机构
[1] North China Elect Power Univ, Sch Elect & Elect Engn, State Key Lab Alternate Elect Power Syst Renewab, Beijing 102206, Peoples R China
[2] State Grid Shanghai Municipal Elect Power Co, Shanghai, Peoples R China
[3] Ibaraki Univ, Sch Sci & Engn, Ibaraki, Japan
[4] Inst Telecomunicacoes, Aveiro, Portugal
关键词
Digital twin; low-carbon smart park; federated learning; resource management; ALLOCATION;
D O I
10.1109/ICC45855.2022.9838789
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
The low-carbon operation of smart park requires to deploy massive internet of things (IoT) devices to provide real-time monitoring and control services. Digital twin (DT) provides accurate guidance for communication network resource management in low-carbon smart park by establishing a digital representation of physical entities. Facing the strict requirements of DT on delay and accuracy, as well as the constraints of access priority and energy consumption, we propose a federated learning-based DT framework and a Latency-awarE diGital twIn assisted resOurce maNagement algorithm (LEGION). LEGION can achieve a well tradeoff between delay and accuracy performances under the long-term constraints of access priority and energy consumption. Compared with existing algorithms, LEGION has superior performance in average iteration delay, DT loss function, energy consumption, and access priority deficit.
引用
收藏
页码:2942 / 2947
页数:6
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