Active Flows in Diagnostic of Troubleshooting on Backbone Links

TL;DR

This paper proposes using the number of active flows as a proxy for network utilization to identify overload conditions on backbone links, providing a practical diagnostic tool for troubleshooting network issues.

Contribution

It introduces a novel approach to diagnose network overload by analyzing active flows and formulates an easy rule for defect detection based on router measurements.

Findings

Active flows effectively indicate network utilization levels.

Gaussian approximation helps define confidence intervals for operational regions.

The method enables proactive troubleshooting of backbone links.

Abstract

This paper aims to identify the operational region of a link in terms of its utilization and alert operators at the point where the link becomes overloaded and requires a capacity upgrade. The number of active flows is considered the real network state and is proposed to use a proxy for utilization. The Gaussian approximation gives the expression for the confidence interval on an operational region. The easy rule has been formulated to display the network defects by means of measurements of router loading and number of active flows. Mean flow performance is considered as the basic universal index characterized quality of network services provided to single user.