Optical networks: a practical perspective
Optical networks: a practical perspective
Network Management: An Introduction to Principles and Practice
Network Management: An Introduction to Principles and Practice
Optical WDM Networks (Optical Networks)
Optical WDM Networks (Optical Networks)
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
Computer Networks: The International Journal of Computer and Telecommunications Networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
Optical Fiber Telecommunications: Systems and Networks
Optical Fiber Telecommunications: Systems and Networks
Guest editorial: bio-inspired networking
IEEE Journal on Selected Areas in Communications
Guest editorial: biologically inspired networking
IEEE Network: The Magazine of Global Internetworking - Special issue on biologically inspired networking
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Optical Switching and Networking
Issues for routing in the optical layer
IEEE Communications Magazine
WDM optical communication networks: progress and challenges
IEEE Journal on Selected Areas in Communications
Cross-layer adaptive routing and wavelength assignment in all-optical networks
IEEE Journal on Selected Areas in Communications - Part Supplement
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We propose a methodology to design the link cost function and, consequently, a systematic form to design a RWA algorithm. We call this methodology link cost function design (LCFD) and it consists of four steps: The choice of the link cost function input variables, the expansion of the cost function in terms of a series, the selection of an overall network performance indicator as the optimization target, and finally, the execution of an optimization process to find the series coefficients that optimize the network performance indicator based on off-line network simulations. The optimization process is performed by a computational intelligence technique, the particle swarm optimization. The proposed methodology (LCFD) is used to design an adaptive IA-RWA algorithm, which we call Power Series Routing (PSR). The effectiveness of both methodology and IA-RWA algorithm is investigated. The PSR is compared with other algorithms found in the literature by means of computational simulations and our proposal presented lower blocking probabilities with shorter computation time. Furthermore, we investigate the sensitivity and the ability of the proposed PSR to adapt itself to topological changes in the network due to both link/node addition/failure. We also investigate the behavior of the PSR in a scenario where the traffic load distribution is randomly chosen (non-uniform traffic), and we compared it to other three routing algorithms.