AI

Sources of Traffic Demand Variability and Use of Monte Carlo for Network Capacity Planning

Abstract

When sizing any network capacity, several factors, such as Traffic, Quality of Service (QoS), and Total Cost of Ownership (TCO) are usually taken into account. Generally, it boils down to a joint minimization of cost and maximization of traffic subject to the constraints of protocol and QoS requirements. Stochastic nature of network traffic and link saturation queueing issues add uncertainty to the already complex optimization problem. In this paper, we examine the sources of traffic demand variability and dive into Monte-Carlo methodology as an efficient way for solving these problems. Other sources of uncertainty in network capacity forecasting are briefly discussed in the Attachment.