A Data and Network Deep Collaboration method for Data Circulation
Naihan Zhang, Xinxin Yi, Ran Pang, Xinrui Gu, Zhengxin Han, Mengyao Han, Chang Cao, Tao Huang, Xiongyan Tang · 2025
A data and network deep collaboration method is proposed for data circulation. In the proposed method, the network controller and data controller collaborate to leverage the wide coverage capability of the network for unified orchestration of cross-domain and cross-entity data circulation. The combination of application-aware network identifier (APN ID) and data ID realizes data awareness by the network, allowing the network to provide users with fine-grained differentiated services. Additionally, innovative IPv6-based techniques, such as differentiated routing, data fences, data customs, path monitoring, and elastic bandwidth transmission, are introduced to provide reliable, efficient, and flexible network capabilities for data circulation. The relevant network capabilities of the proposed method have been validated on China Unicom scientific experiment network. The performance of the APN scheme was also tested, and the experiment shows that the method combining APN ID and data ID is a lightweight and efficient method for identification and processing of the transmitted data packet. Compared with DPI-based methods, the detection time of the proposed method is much lower, which is more suitable for deployment in current networks.