Optimal Scalability of FiWi Networks Based on Multistage Stochastic Programming and Policies

Abstract

The large demand of bandwidth due to new and future applications from services being implemented such as smart grid (SG), smart cities (SC), and the Internet of Things has triggered a focus of interest from the scientific community on issues related to the planning and scalability of the communications infrastructure. In this paper, we present three new and important contributions regarding the deployment of FiWi networks that support users who benefit from the services provided by SG and SC. We first propose a planning model, and then formulate a mixed linear programming optimization model using multistage stochastic programming, and finally propose an algorithm, called MOA–FiWi, which has the capacity to handle medium and large instances of the problem and give feasible solutions for the optimization process, where scalability indices between 85%–95% are reached with respect to the projected stochastic values. The proposed model considers the scalability and capital and operating expense, as well as the uncertainty management in the different stages of time–space through multistage stochastic programming. The proposed model presents flexibility in decision making as the time stages progress. This allows for the planning of green fields, as well as the updating of networks that already have communication infrastructure.