Token service interface coordinates ai and radio networks for drones
A Token Service Interface for AI-Native RANs
Networking and Internet Architecture
Summary
Communication between AI services and wireless networks is complicated because different messages have different timing and state needs. The authors propose a new way to organize and manage these messages using a token service interface that links AI applications, wireless networks, and edge computers. This interface helps schedule messages with the right timing and state, improving communication. They show how this works with drones inspecting something remotely, improving the network's ability to handle important data quickly and efficiently.
What this means in practice
- •For network schedulers: Enable precise scheduling of AI tokens in wireless systems to prioritize important data and meet timing needs.
- •For drone fleet operators: Improve remote drone inspection by coordinating AI commands and data delivery to minimize delays and interruptions.
Authors
Jianan Zhang, Peng Li, Xiang Cheng
Abstract
Generative and embodied AI services exchange token streams within continuing inference and control loops. Their communication requirements depend on each token set's purpose, useful timing, and execution context. This article organizes these properties into service, temporal, and stateful semantics and proposes a token service interface (TSI) between applications, radio access networks (RANs), and edge runtimes. TSI binds delivery requirements, readiness forecasts, and execution-state references to each schedulable token set, specifying field ownership, versioned updates, and admission feedback. A drone inspection case study over a decoupled RAN illustrates importance-aware radio allocation, advance preparation for timely delivery, and selective state migration that balances interruption against forwarding delay.