6G network technology will emerge in a landscape where visual data transmissions dominate global mobile traffic and are expected to grow continuously, driven by the increasing demand for AI-based computer vision applications. This will make already challenging task of visual data transmission even more difficult. In this work, we review effective techniques for visual data transmission, such as content compression and adaptive video streaming, highlighting their advantages and limitations. Further, considering the scalability and cost issues of cloud-based and on-device AI services, we explore distributed in-network computing architecture like fog-computing as a direction of 6G networks, and investigate the necessary technical properties for the timely delivery of visual data.

翻译：6G网络技术将在一个视觉数据传输主导全球移动流量并有望持续增长的背景下应运而生，这主要受到基于AI的计算机视觉应用需求不断增长的驱动。这将使得本已具有挑战性的视觉数据传输任务变得更加困难。本文回顾了视觉数据传输的有效技术，例如内容压缩与自适应视频流传输，并重点阐述了其优势与局限性。此外，考虑到基于云和设备的AI服务的可扩展性与成本问题，我们探讨了雾计算等分布式网络内计算架构作为6G网络的发展方向，并研究了实现视觉数据及时交付所需的关键技术特性。