On optimizing Inband Telemetry systems for accurate latency-based service deployments

TL;DR

This paper presents a telemetry methodology for collecting accurate latency data, which is essential for developing intelligent control planes in zero-touch network management systems.

Contribution

It introduces a novel telemetry approach to improve latency measurement accuracy, supporting the advancement of AI-driven network automation.

Findings

Proposes a new telemetry methodology for latency measurement

Demonstrates improved accuracy in latency data collection

Supports development of intelligent control planes

Abstract

The power of Machine Learning and Artificial Intelligence algorithms based on collected datasets, along with the programmability and flexibility provided by Software Defined Networking can provide the building blocks for constructing the so-called Zero-Touch Network and Service Management systems. However, the fuel towards this goal relies on the availability of sufficient and good-quality data collected from measurements and telemetry. This article provides a telemetry methodology to collect accurate latency measurements, as a first step toward building intelligent control planes that make correct decisions based on precise information.