Optimization problems in WDM optical transport networks with scheduled lightpath demands

Wavelength division multiplexing optical transport networks are expected to provide the capacity required to satisfy the growing demand of telecommunications traffic in a cost-effective way. These networks, based on standards and implementation agreements currently under development by the ITU-T, the IETF and the OIF, are likely to be deployed during the next 5 or 6 years. New optimization problems arise in connection with these networks for several reasons. Firstly, the cost of optical networking equipment is not still well known due mainly to the early stage of development of the relevant technologies. Secondly, the uncertainty of traffic demands, due to the competition in the telecommunications market and to the massive adoption of new data applications, render difficult the accurate dimensioning of networks. Finally, the early stage of development of optical technology results in new functional constraints that must be taken into account during the design and dimensioning of the network. We investigate optimization problems arising in the engineering of an optical transport network. Network engineering concerns the configuration of existing network resources in order to satisfy expected traffic demands. Unlike network planning and traffic engineering, network engineering problems are relevant at time scales ranging from hours to weeks. A these time scales, the dynamic evolution of the traffic load is an important factor that must be taken into account in the configuration of the network. Moreover, the periodicity of the traffic load evolution observed in operational transport networks suggest that the traffic may be modeled deterministically. We propose a dynamic deterministic traffic model called Scheduled Lightpath Demands (SLDs). An SLD is a connection demand represented by a tuple (s, d, n, alpha, omega) where s and d are the source and destination nodes of the demand, n is the number of requested connections and alpha, omega are the set-up and tear-down dates of the requested connections. The model captures the time and space distribution of a set of connection demands and, being deterministic,eases the use of combinatorial optimization techniques to solve network optimization problems. We investigate three network optimization problems involving the SLD traffic model: - We first study the Routing and Wavelength Assignment (RWA) for SLDs problem in a wavelength-switching network. The routing problem is formulated as a combinatorial optimization problem with two possible objective functions. We propose a Branch & Bound (B&B) and a Tabu Search (TS) algorithm that compute, respectively, exact and approximate solutions. Wavelength assignment is formulated as a graph coloring problem. We use an existing greedy algorithm to find approximate solutions. - We then investigate the problem of Diverse Routing and Spare Capacity Assignment (DRSCA) for SLDs in a wavelength-switching network. The problem consists of defining a pair of span-disjoint paths for each SLD so that the number of required working and spare channels is minimal. We propose a channel reuse technique to reduce the required working channels and a backup multiplexing technique to reduce the spare channels required for protection. The problem is formulated as a combinatorial optimization problem. We propose a Simulated Annealing (SA) meta-heuristic algorithm to compute approximate solutions. - Finally, we investigate the problem of Routing and grooming of SLDs (SRG) in a multi-granularity switching network. We consider a network whose nodes have a wavelength cross-connect (WXC) and a waveband cross-connect (BXC). The problem is formulated as a combinatorial optimization problem. We propose a parallel TS meta-heuristic algorithm to compute approximate solutions. We determine the conditions under which a network based on multi-granularity switches is more economical than a wavelength-switching (single-granularity) network.