Ant colony optimization for dynamic routing and wavelength assignment in WDM networks with sparse wavelength conversion

• Published in: Engineering applications of artificial intelligence Vol. 24; no. 2; pp. 295 - 305
• Main Authors: Chen, Ming-Tsung, Lin, Bertrand M.T., Tseng, Shian-Shyong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2011
• Subjects: Algorithms; Ant colony optimization; Approximate solution; Combinatorial analysis; Communication cost; Computer networks; Delay; Delay bound; Mathematical models; Networks; Optimization; Routing (telecommunications); Routing and wavelength assignment; Wavelengths; Delay bound; Ant colony optimization; Approximate solution; Routing and wavelength assignment; Communication cost
• ISSN: 0952-1976; 1873-6769
• DOI: 10.1016/j.engappai.2010.05.010

Since optical WDM networks are becoming one of the alternatives for building up backbones, dynamic routing, and wavelength assignment with delay constraints (DRWA-DC) in WDM networks with sparse wavelength conversions is important for a communication model to route requests subject to delay bounds. Since the NP-hard minimum Steiner tree problem can be reduced to the DRWA-DC problem, it is very unlikely to derive optimal solutions in a reasonable time for the DRWA-DC problem. In this paper, we circumvent to apply a meta-heuristic based upon the ant colony optimization (ACO) approach to produce approximate solutions in a timely manner. In the literature, the ACO approach has been successfully applied to several well-known combinatorial optimization problems whose solutions might be in the form of paths on the associated graphs. The ACO algorithm proposed in this paper incorporates several new features so as to select wavelength links for which the communication cost and the transmission delay of routing the request can be minimized as much as possible subject to the specified delay bound. Computational experiments are designed and conducted to study the performance of the proposed algorithm. Comparing with the optimal solutions found by an ILP formulation, numerical results evince that the ACO algorithm is effective and robust in providing quality approximate solutions to the DRWA-DC problem.