A Genetic Algorithm Approach to the Grooming of Dynamic Traffic in Tree and Star Networks with Bifurcation

TL;DR

This paper introduces a genetic algorithm-based method for dynamic traffic grooming in WDM tree and star networks, utilizing bifurcation techniques to optimize resource usage and reduce equipment and wavelength requirements.

Contribution

It proposes novel splitting methods and a genetic algorithm approach for efficient dynamic traffic grooming in non-blocking tree and star networks.

Findings

Algorithm effectively reduces ADMs and wavelengths.

Performance tested under various network conditions.

Simulation results confirm efficiency and effectiveness.

Abstract

Traffic grooming is widely employed to reduce the number of ADM's and wavelengths. We consider the problem of grooming of dynamic traffic in WDM tree and star networks in this paper. To achieve better results, we used the bifurcation techniques to the grooming of arbitrary dynamic traffic in a strictly non-blocking manner in networks. Three splitting methods, including Traffic-Cutting, Traffic-Dividing and Synthesized-Splitting were proposed. A genetic algorithm (GA) approach based on these methods was proposed to tackle such grooming problems in tree and star networks. The performance of these algorithms was tested under different conditions in star and tree networks. Computer simulation results showed that our algorithm is efficient in reducing both the numbers of ADM's and wavelengths.