Grooming of Dynamic Traffic in WDM Star and Tree Networks Using Genetic Algorithm

TL;DR

This paper presents a genetic algorithm approach for dynamic traffic grooming in WDM star and tree networks, effectively reducing the number of ADMs and wavelengths under changing traffic conditions.

Contribution

It introduces a novel GA-based method for dynamic traffic grooming in star and tree networks, with derived bounds and simulation validation.

Findings

The algorithm reduces ADM count significantly.

It minimizes wavelength usage effectively.

Simulation results confirm efficiency.

Abstract

The advances in WDM technology lead to the great interest in traffic grooming problems. As traffic often changes from time to time, the problem of grooming dynamic traffic is of great practical value. In this paper, we discuss dynamic grooming of traffic in star and tree networks. A genetic algorithm (GA) based approach is proposed to support arbitrary dynamic traffic patterns, which minimizes the number of ADM's and wavelengths. To evaluate the algorithm, tighter bounds are derived. Computer simulation results show that our algorithm is efficient in reducing both the numbers of ADM's and wavelengths in tree and star networks.