Intent-Driven Control System for Heterogeneous Agent-Oriented Networking (HaoNet)

Abstract: Empowered by advances in large language models, the growing integration of autonomous agents into industrial and daily-life sectors is turning them into new networking entities. Such agent-oriented networking features high interaction frequencies and emergent task-driven struc‑ tures, necessitating strong network policy consistency and reliability within dynamic environments. To address these challenges, we propose a net‑ work control system that integrates Intent-Driven Network (IDN) into Heterogeneous Agent-Oriented Networking (HaoNet). IDN focuses on high- level task intents and provides flexible reconfiguration and adaptive optimization, thereby enhancing the effectiveness of agent-oriented network‑ ing. In this paper, we first summarize three key features of HaoNet: task-driven operation, distributed collaboration, and closed-loop intelligence. Furthermore, we propose a comprehensive system architecture, which includes the application layer, the intent layer, and the infrastructure layer, and investigate the associated key technologies. Finally, typical application scenarios are presented to demonstrate the practical value of the pro‑ posed system in enabling robust agent-oriented networking control.

Keywords: AI agent; agent-oriented networking; intent-driven network; network control