On Planning of Optical Networks and Representation of their Uncertain Input Parameters

Abstract

This paper studies the use of uncertain inputs in the strategic network planning process. To model uncertain planning inputs three essential parameters are needed the predicted value expressing for instance an expert’s view, the uncertainty level indicating the doubt there is about the predicted value, and the confidence parameter denoting the probability that the output parameter was estimated big enough (compared to the actual output). Several planning approaches that handle uncertain variables are distinguished and their strengths and shortcomings are indicated. This allows to indicate the pitfalls in some common planning practices that use a fixed safety margin to handle uncertainty. It is shown that they can lead to incorrect planning decisions, such as underestimation of the impact of the input uncertainty and overdimensioning in case of inaccurately modelled dimensioning problems. Both a theoretic model and simulation results are shown. A real-life planning problem is studied, including forecasting future network traffic from uncertain inputs and dimensioning a network to accommodate an uncertain traffic demand.