General artificial intelligence enables network intelligence: a network operating system based on large language model - HUO Ru; SHA Zongxuan; LYU Kecheng; CHEN Wei; WANG Shuo; HUANG Tao; YU F. Richard (Tongxin xuebao)
To achieve the goal of highly intelligent and controllable network, and a highly controllable large-scale network operating system was proposed based on large language model (LLM). Through network situation awareness and the intention understanding of fine-tuning LLM, resource allocation was optimized to achieve intelligent operation and maintenance. Meanwhile, the fine-tuning and inference flow for China network operation system (CNOS) oriented network large model was designed to recognize the CNOS system instructions and summarize the feedback results of the system, as well as periodic autonomous training and iterative model updating. The experimental results show that the proposed system can quickly identify and accurately convert user instructions, effectively reduce the management task time of the operating system, realize the intelligent scheduling and configuration of network resources, and improve the controllability of the network operating system and the friendliness of human-computer interaction.