Digital Twin-Driven Network Architecture for Video Streaming

被引:1
|
作者
Huang, Xinyu [1 ]
Yang, Haojun [1 ]
Hu, Shisheng [1 ]
Shen, Xuemin [1 ]
机构
[1] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
来源
IEEE NETWORK | 2024年 / 38卷 / 06期
关键词
Streaming media; Three-dimensional displays; Sensors; Real-time systems; Network slicing; Artificial intelligence; Solid modeling; Digital twin (DT); video streaming; holistic network virtualization; network slicing; native AI; COMMUNICATION;
D O I
10.1109/MNET.2024.3386030
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Digital twin (DT) is revolutionizing the emerging video streaming services through tailored network management. By integrating diverse advanced communication technologies, DTs are promised to construct a holistic virtualized network for better network management performance. To this end, we develop a DT-driven network architecture for video streaming (DTN4VS) to enable network virtualization and tailored network management. With the architecture, various types of DTs can characterize physical entities' status, separate the network management functions from the network controller, and empower the functions with emulated data and tailored strategies. To further enhance network management performance, three potential approaches are proposed, i.e., domain data exploitation, performance evaluation, and adaptive DT model update. We present a case study pertaining to DT-assisted network slicing for short video streaming, followed by some open research issues for DTN4VS.
引用
收藏
页码:334 / 341
页数:8
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