Forecasting of access network bandwidth demands for aggregated subscribers using Monte Carlo methods

Abstract

In the face of relentless growth in traffic, network operators must continuously forecast bandwidth demand to properly dimension their networks and make the correct investments for the future. The consequences of under-investing are poor network performance and dissatisfied subscribers, while over-investing ties up capital that could have been better spent elsewhere. In this article we describe a model that forecasts bandwidth demands of aggregated subscribers on residential fixed access networks. For sustained bandwidth demand, we use statistical techniques to quantify the number of concurrent video streams, the shifting mix of standard definition, high definition, and ultra high definition resolutions, multicast gain, and the trend from multicast to unicast delivery of these streams. Mechanisms to cope with bursty bandwidth demand are included. The results we report can guide operators in making technology and network design choices for future FTTx deployments.