Title :
Forecasting of access network bandwidth demands for aggregated subscribers using Monte Carlo methods
Author :
Harstead, Ed ; Sharpe, Randy
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.
Keywords :
Monte Carlo methods; statistical analysis; subscriber loops; telecommunication traffic; Monte Carlo method; access network bandwidth demands forecasting; aggregated subscribers; concurrent video streams; multicast gain; residential fixed access networks; statistical techniques; ultra high definition resolutions; unicast delivery; Bandwidth; Bit rate; Forecasting; High definition video; Monte Carlo methods; Streaming media; Telecommunication traffic;
Journal_Title :
Communications Magazine, IEEE
DOI :
10.1109/MCOM.2015.7060505