Abstractions for Network Intelligence: A Reference Architecture for AI at the Wireless Edge
2026-08-10 • Networking and Internet Architecture
Networking and Internet Architecture
AI summaryⓘ
The authors propose a new architecture called AI-EDGE that helps networks and AI applications work better together by sharing important information. This design creates a common system layer to enable smarter interaction between the network and AI software, especially in wireless and edge computing environments. They explain how this setup can be tested on current platforms and show examples of how different users can benefit from improved network awareness, easier app movement, and quicker development. Overall, the authors aim to make networks and AI more cooperative and efficient.
AI-EDGE architectureintelligent networkedge computingO-RAN3GPP Edge AppETSI MECnetwork awarenessportabilityreference architectureinformation waist
Authors
Salil Reddy, Haohuang Wen, Ness Shroff, Venki Ramaswamy, Zhiqiang Lin, Elisa Bertino, Jim Kurose, Anish Arora
Abstract
Networks are increasingly adopting AI as are AI applications leveraging networks. Awareness sharing between networks and AI applications promises to unlock higher levels of network utilization and application performance, but is inadequately supported in the current architecture of the Internet. In this paper, we describe a reference architecture that abstractly enables the synergistic interaction of intelligent applications and the intelligent network, via an information waist, and also supports the network intelligence services in the emerging intelligence plane in networks. We discuss the rationale for our AI-EDGE architecture, its functional requirements, and the core abstractions. We present a reference component-level design of the core abstractions to support experimentation and development on existing platforms for wireless networking (i.e., based on O-RAN cellular networks) and edge computing (i.e., based on 3GPP Edge App and ETSI MEC). Moreover, we provide representative use cases from the perspective of different types of users that demonstrate the benefits of the architecture in contexts of awareness sharing, portability, prototyping, and validation.