A genetic algorithm for dynamic routing and wavelength assignment in WDM networks

• Published in: Lecture notes in computer science pp. 893 - 902
• Main Authors: Le, Vinh Trong, Ngo, Son Hong, Jiang, Xiaohong, Horiguchi, Susumu, Guo, Minyi
• Format: Conference Proceeding Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer-Verlag 01.01.2004; Springer Berlin Heidelberg; Springer
• Series: ACM Conferences
• Subjects: Applied sciences; Blocking Probability; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Computing methodologies; Computing methodologies > Artificial intelligence; Computing methodologies > Artificial intelligence > Search methodologies; Computing methodologies > Artificial intelligence > Search methodologies > Heuristic function construction; Connection Request; Dynamic Routing; Exact sciences and technology; Improve Genetic Algorithm; Networks; Networks > Network protocols; Networks > Network protocols > Network layer protocols; Networks > Network protocols > Network layer protocols > Routing protocols; Software; Theory of computation; Theory of computation > Design and analysis of algorithms; Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis; Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis > Routing and network design problems; Wavelength Assignment; Routing algorithm; Parallel algorithm; Network topology; Probabilistic approach; Genetic algorithm; Wavelength division multiplexing; Routing; Cost estimation; Distributed computing; Simulator; Route; Wavelength
• ISBN: 9783540241287; 3540241280
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-30566-8_103

In this paper, we study the challenging problem of Dynamic Routing and Wavelength Assignment (DRWA) in WDM (Wavelength-Division-Multiplexing) networks with wavelength continuity constraint, and propose an improved genetic algorithm (GA) for it. By adopting a new fitness function to consider simultaneously the path length and number of free wavelengths in cost estimation of a route, the new genetic RWA algorithm can achieve a good load balance among route candidates and result in a lower blocking probability than both the fixed alternative routing algorithm and the previous GA-based algorithm for DRWA, as verified by an extensive simulation study upon the ns-2 network simulator and some typical network topologies.