Wavelength assignment using a hybrid evolutionary computation to reduce cross-phase modulation

• Autor(a) principal: MIRANDA, André Moacir Lage
• Data de Publicação: 2014
• Outros Autores: LIMA, Fabio de Oliveira, ROCHA, Helder Roberto de Oliveira, VIJAYKUMAR, Nandamudi Lankalapalli, FRANCÊS, Carlos Renato Lisboa, SEGATTO, Marcelo Eduardo Vieira, COSTA, João Crisóstomo Weyl Albuquerque
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFPA
• Texto Completo: http://repositorio.ufpa.br/jspui/handle/2011/6294
• topic: Modulação de fase cruzada; Redes ópticas; Algoritmos genéticos; Computação evolutiva

In this paper, we propose a hybrid methodology based on Graph-Coloring and Genetic Algorithm (GA) to solve the Wavelength Assignment (WA) problem in optical networks, impaired by physical layer effects. Our proposal was developed for a static scenario where the physical topology and traffic matrix are known a priori. First, we used fixed shortest-path routing to attend demand requests over the physical topology and the graph-coloring algorithm to minimize the number of necessary wavelengths. Then, we applied the genetic algorithm to solve WA. The GA finds the wavelength activation order on the wavelengths grid with the aim of reducing the Cross-Phase Modulation (XPM) effect; the variance due to the XPM was used as a function of fitness to evaluate the feasibility of the selected WA solution. Its performance is compared with the First-Fit algorithm in two different scenarios, and has shown a reduction in blocking probability up to 37.14% when considered both XPM and residual dispersion effects and up to 71.42% when only considered XPM effect. Moreover, it was possible to reduce by 57.14% the number of wavelengths.