Digital-Twin-Enabled On-Demand Content Delivery in HetVNets

被引:7
|
作者
Hui, Yilong [1 ]
Qiu, Yi [1 ]
Cheng, Nan [1 ]
Yin, Zhisheng [2 ]
Chen, Rui [1 ]
Liang, Kai [1 ]
Luan, Tom H. [3 ]
机构
[1] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
[2] Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
[3] Xi An Jiao Tong Univ, Sch Cyber Sci & Engn, Xian 710049, Peoples R China
基金
中国博士后科学基金;
关键词
Content delivery; digital twins (DTs); game theory; heterogeneous vehicular networks (HetVNets); vehicular networks; VEHICULAR NETWORKS; SATELLITE; COMMUNICATION;
D O I
10.1109/JIOT.2023.3245661
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The heterogeneous vehicular networks (HetVNets) can accelerate the deployment of Internet of Vehicles (IoV) and enrich the content distribution methods. However, the diverse requirements of vehicular users (VUs), the limited cache resources of roadside units (RUs), and the frequent interactions between VUs and RUs pose great challenges to efficiently distribute contents. To address these challenges, we propose an on-demand content delivery scheme in digital twin-enabled HetVNets (DT-HetVNets). Specifically, we first design an on-demand content delivery architecture in DT-HetVNets which uses DT communication mode to simplify the frequent interactions between VUs and RUs. With this architecture, by jointly considering the popularity of each content and the relevance between different contents, the personal content requirement of each DT of VU (DT-VU) can be perceived and the VUs within the coverage of the same RU can collaboratively request contents in groups. Then, we formulate the interaction between each group and the DT of the RU (DT-RU) as a double auction game to determine the transaction price of the perceived content, where the request information of the contents which are accepted by the groups can be shared between different DT-RUs based on the path of each group, enabling collaborative content recommendation between the RUs. After that, by jointly considering the contents recommended by different DT-RUs and the content popularity, the content caching model of each DT-RU is formulated as a knapsack problem, where a collaborative content caching algorithm is designed to obtain the optimal caching strategy with the target of making full use of the limited cache resources. Compared with the conventional schemes, the simulation results show that our scheme can not only bring the highest utility to the RUs but also lead to the highest hit ratio and the lowest delay.
引用
收藏
页码:14028 / 14041
页数:14
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