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Abstract

The rapid change in traffic behavior and the tremendous growth in bandwidth demand have promoted the development of a new generation of optical networks known as elastic optical networks (EONs). EONs provide scalable, flexible, and efficient assignment of network resources. Spectrum allocation is one of the most important factors in the success of EONs. In this study, we propose an adaptive spectrum allocation algorithm for EONs in the case of multicasting. The algorithm is based on relative cost and learning automata to produce a near-optimal searching sequence of the optical spectrum. The algorithm estimates the net margin of carrying a call at a set of contiguous frequency slots on subsequent (future) call arrival. This margin will be used to sort the spectrum frequencies. Simulation results show that our algorithms outperform existing algorithms and provide savings for the normalized revenue loss of up to 50% over the static first-fit spectrum allocation algorithm.

Keywords

Elastic optical networks routing and spectrum allocation learning automata multicast

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Adaptive spectrum allocation algorithm for elastic optical networks with multicasting

Abstract

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