AI

WAN Capacity Forecasting for Large Enterprises

Abstract

This paper presents the framework for capacity forecast of a large enterprise to enable accurate and reliable prediction of WAN requirements for all enterprise offices. Quarterly forecasts are generated for individual offices in an enterprise network using historical bandwidth utilization for the offices and their associated usage headcount. This framework is currently used to inform WAN circuit upgrade/downgrade decision for more than 80 offices, and more than 200 associated circuits. The framework uses statistical regression models to create 6, 12, and 24 months forecast for each office, and rigorously evaluates the forecast accuracy with real data.