Artificial Intelligence (AI) for Network Operations
draft-king-rokui-ainetops-usecases-01
| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
|
|
|---|---|---|---|
| Authors | Reza Rokui , Cheng Li , Daniel King | ||
| Last updated | 2026-03-19 (Latest revision 2025-09-15) | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
Abstract
This document explores the role of the IETF and IRTF in advancing Artificial Intelligence for network operations (AINetOps), focusing on requirements for IETF protocols and architectures. AINetOps applies AI/ML techniques to automate and optimize network operations, enabling use cases such as reactive troubleshooting, proactive assurance, closed-loop optimization, misconfiguration detection, and virtual operator assistance. The document addresses AINetOps for both single-layer IP or Optical networks and multi-layer IP/Optical networks. It defines the concept of AINetOps for networking and provides its operational benefits such as network assurance, predictive analytics, network optimization, multi-layer planning, and more. It aims to guide the evolution of IETF protocols to support AINetOps-driven network management.
Authors
Reza Rokui
Cheng Li
Daniel King
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)