Inband Flow Learning Framework
draft-hwy-opsawg-ifl-framework-04
| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
|
|
|---|---|---|---|
| Authors | Liuyan Han , Minxue Wang , Xuanxuan Wang , Tianran Zhou | ||
| Last updated | 2024-01-27 (Latest revision 2023-07-27) | ||
| 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This Internet-Draft is no longer active.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
On-path telemetry techniques can provide high-precision inband flow insight and real-time network performance monitoring by embedding instructions or metadata into user packets. They are benificial but still has problems of deployability and flexibility in large scale deployment scenario. This document proposes a reference framework called Inband Flow Learning (IFL), which outlines the architecture and functional modules for automatic deployment and adjustment of flow-oriented monitoring using on-path telemetry techniques, trying to provide a solution for reference to solve the problems. This document also provides different deployment approaches and considerations in practical network deployment.
Authors
Liuyan Han
Minxue Wang
Xuanxuan Wang
Tianran Zhou
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)