WAVELENGTH ASSIGNMENT USING A HYBRID EVOLUTIONARY COMPUTATION TO REDUCE CROSS-PHASE MODULATION

Authors

  • André M. L. Miranda
  • Fabio de O. Lima
  • Helder R. de O. Rocha
  • Nadamudi Vijaykumar
  • Carlos R. L. Francês
  • Marcelo E. V. Segatto
  • João C. W. A. Costa

DOI:

https://doi.org/10.1590/S2179-10742014000100001

Keywords:

Cross-Phase Modulation, Dense Wave Division Multiplex, Evolutionary Computation, Wavelength Assignment Algorithms.

Abstract

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 ï¬xed 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

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Published

2014-08-01

How to Cite

André M. L. Miranda, Fabio de O. Lima, Helder R. de O. Rocha, Nadamudi Vijaykumar, Carlos R. L. Francês, Marcelo E. V. Segatto, & João C. W. A. Costa. (2014). WAVELENGTH ASSIGNMENT USING A HYBRID EVOLUTIONARY COMPUTATION TO REDUCE CROSS-PHASE MODULATION. Journal of Microwaves, Optoelectronics and Electromagnetic Applications (JMOe), 13(1), 1–15. https://doi.org/10.1590/S2179-10742014000100001

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