Applications of Computational Intelligence to Impairment-Aware Routing and Wavelength Assignment in Optical Networks

Applications of Computational Intelligence to Impairment-Aware Routing and Wavelength Assignment in Optical Networks

Joaquim F. Martins-Filho (Federal University of Pernambuco, Brazil), Carmelo J. A. Bastos-Filho (University of Pernambuco, Brazil), Daniel A. R. Chaves (Federal University of Pernambuco, Brazil) and Helder A. Pereira (University of Pernambuco, Brazil)
DOI: 10.4018/978-1-4666-3652-1.ch009
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Computational intelligence techniques have been used to solve hard problems in optical networks, such as the routing and wavelength assignment problem, the design of the physical and the logical topology of these networks, and the placement of some high cost devices along the network when it is necessary, such as regenerators and wavelength converters. In this chapter, the authors concentrate on the application of computational intelligence to solve the impairment-aware routing and wavelength assignment problem. They present a brief survey on this topic and a detailed description and results for two applications of computational intelligence, one to solve the wavelength assignment problem with an evolutionary strategy approach and the other to tackle the routing problem using ant colony optimization.
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Wavelength routed optical networks have been considered as the most reliable and economic solution to achieve high transmission capacities with Quality of Service (QoS). In these networks, the signal remains in the optical domain between the edge nodes, i.e. the signal propagates along the core of the optical network without any optical-electrical-optical conversion. One of the main challenges in these optical networks is to define an appropriate RWA algorithm in order to obtain a low blocking probability with an acceptable Quality of Transmission (QoT) for every established lightpath. A suitable impairment-aware RWA algorithm has to find a route and select a wavelength between the source-destination nodes that provides a minimum QoT for every network request, taking into account the impairments imposed by the physical layer. Besides, the RWA algorithm needs to consider the efficient utilization of network resources and the optimization of the network performance (Rahbar, 2011; Azodolmolky, 2009; Martinez, 2006).

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