Stochastic programming methods applied to network optimization

As communication technologies evolve, it becomes necessary to incorporate the stochastic effect of traffic flows into network models. This paper introduces the stochastic programming (SP) methodology for characterizing traffic. Two SP approaches, here-and-now (HN) and scenario tracking (ST), are described through case studies for a prototype network. A numerical optimization procedure is used to perform the simulation. It is clearly demonstrated that when the probability distributions can be estimated analytically, the HN approach can be attractive. Otherwise, the ST approach may be more appropriate.