HEURISTIC AND BIO-INSPIRED METHODS FOR OPTIMIZING SPECTRUM ALLOCATION AND SPLIT SPECTRUM IN ELASTIC OPTICAL NETWORKS.
Elastic optical networks, MSCL, Split-spectrum, Evolutionary Algorithms, Routing, Spectrum allocation.
Optical networks appear as one of the main infrastructure for transporting large amounts of data in current times. Among most studied optical technologies investigated in recent works we can mention Elastic optical networks, which show outstanding use of spectrum due to the possibility of working with variable-bandwidth requests. The present work deals with the use of heuristics and meta-heuristics for improvements in routing and spectrum assignment in Elastic optical networks. A routing and spectrum assignment scheme based on Split Spectrum for single and multiple paths is initially proposed, which is capable of increasing network availability by reducing the loss of options for inserting requests in the route frequency spectrum, with the consequent mitigation of blocking probability of next requests. It is also proposed a meta-heuristic based on Particle Swarm Optimization (PSO) with the objective of defining solutions for the spectrum assignment in Elastic optical networks, using the algorithm known as MSCL (Min Slot-Continuity Capacity Loss) and an optimization methodology by series of functions. This scheme takes into account the peculiarities of each route in the network, grouping common characteristics so that it can be used to obtain matrices with optimized input parameters, in a more adequate way for the capacity loss calculation by the algorithm, also modifying the way of calculating the cost of allocation in such networks, observing the possibilities of improvements with the use of optimization algorithms.