New Data Network Architecture: From Reactive Post-collecting to Intelligent Proactive Pre-sensing

Pengyu Li, Yanxia Xing
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Abstract

With the emergence of scenarios that consume large amounts of data such as AI/ML (artificial intelligence and machine learning) and ISAC (Integrated sensing and communication) technologies, how to efficiently utilize data while protecting data privacy and security, reducing communication overhead, and improving data utilization efficiency have become one of the major research interests for 6G network technologies. Current mobile communication networks only use external data service nodes, and the sensing of data is based on consumer subscription, which cannot meet the data service requirements of 6G networks. We propose a data service network architecture for mobile communication networks that supports intelligent collaboration of distributed data service nodes; transforms reactive subscription mode into proactive sensing mode with the assistance of AI/ML analysis; enhances data sensing, processing and storage mechanisms through the flexible use of data rules and knowledge, thus effectively improving the overall data service capability; further, with this architecture, possible solutions are discussed in detail with emphasis on data sensing difficulties.
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新的数据网络架构:从被动后采集到智能主动预感知
随着AI/ML(人工智能与机器学习)、ISAC(集成传感与通信)技术等大量数据消耗场景的出现,如何在保护数据隐私与安全的同时高效利用数据,降低通信开销,提高数据利用效率,成为6G网络技术的主要研究方向之一。目前的移动通信网络仅使用外部数据服务节点,数据的感知基于消费者订阅,无法满足6G网络的数据业务需求。提出了一种支持分布式数据服务节点智能协同的移动通信网络数据服务网络架构;在AI/ML分析的辅助下,将被动订阅模式转变为主动感知模式;通过灵活运用数据规则和知识,增强数据感知、处理和存储机制,有效提升整体数据服务能力;此外,在此架构下,详细讨论了可能的解决方案,重点是数据感知困难。
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