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.