Topology design and resource dimensioning for optical mesh networks under demand uncertainties

We present a framework to help the network designer to dimension optical metropolitan area networks (MAN) incorporating uncertainties in demands. In this framework the interplay among topology design, resource provisioning, and routing are analyzed jointly, based on two stochastic optimization models that use probability distributions of demands as inputs. In one model we minimize the weighted sum of network installation cost and expected penalty cost for unsatisfied traffic; in another model we minimize the network installation cost subject to certain service level requirements. The optimization results enable us: (1) to identify the physical architectures that are most robust (in cost) to demand uncertainties among rich classes of regular topologies, assuming the (random) uniform all-to-all traffic; and (2) to provide analytical references on how the optimum dimensioning, network connectivity, and network cost change as functions of the designer's level of risk aversion, service level requirements, and probability distributions of the demand