The traditional role of the network layer is the transfer of packet replicas from source to destination through intermediate network nodes. We present a generative network layer that uses Generative AI (GenAI) at intermediate or edge network nodes and analyze its impact on the required data rates in the network. We conduct a case study where the GenAI-aided nodes generate images from prompts that consist of substantially compressed latent representations. The results from network flow analyses under image quality constraints show that the generative network layer can achieve an improvement of more than 100% in terms of the required data rate.

翻译：传统网络层的核心功能是通过中间网络节点将数据包副本从源端传输至目的端。本文提出一种利用中间或边缘网络节点部署生成式人工智能（GenAI）的生成式网络层，并分析其对网络所需数据传输速率的影响。通过案例研究，我们考察了GenAI辅助节点如何基于由高度压缩的潜在表征构成的提示词生成图像。在图像质量约束下进行的网络流量分析结果表明，生成式网络层在所需数据传输速率方面可实现超过100%的优化提升。