Firefly Algorithm Based Optimization Model for Planning of Optical Transport Networks

Abstract

The growth in data traffic is raising serious challenges for OTN in terms of improving their capacity efficiency in order to meet the new traffic requirements. Under these circumstances, the task of efficiently utilizing available resources opens opportunities for the development of a variety of techniques for network planning. This paper presents a decision support system for the optical transport network. It is considered the optical transport network planning problem where a traffic interest matrix between the demand nodes is specified. The network is modeled as a graph, through the arc-path approach. An Integer Linear Programming problem solved with a Firefly Algorithm is proposed for network planning, considering cost minimization. The main novelties of the proposed ILP model is that it accomplishes the optical network design with the possibility of multiple destinations of the traffic matrix and with dynamic allocation of the transmission system modularity. To solve the ILP optimization model the firefly algorithm, genetic algorithm and the exact method are used. Simulations are carried out to verify the performance of the bio-inspired algorithms in relation to the exact method. The results obtained with the firefly algorithm surpass those of the genetic algorithm and approximate the optimal result.

Keywords

• artificial intelligence
• communication networks
• genetic algorithms
• optical fiber networks
• optimization