Increasing demand in the backbone Dense Wavelength Division (DWDM) Multiplexing network traffic prompts an introduction of new solutions that allow increasing the transmission speed without significant increase of the service cost. In order to achieve this objective simpler and faster, DWDM network reconfiguration procedures are needed. A key problem that is intrinsically related to network reconfiguration is that of the quality of transmission assessment. Thus, in this contribution a Machine Learning (ML) based method for an assessment of the quality of transmission is proposed. The proposed ML methods use a database, which was created only on the basis of information that is available to a DWDM network operator via the DWDM network control plane. Several types of ML classifiers are proposed and their performance is tested and compared for two real DWDM network topologies. The results obtained are promising and motivate further research.
Ultra-wideband wavelength division multiplexed networks enable operators to use more effectively the bandwidth offered by a single fiber pair and thus make significant savings, both in operational and capital expenditures. The main objective of this study is to minimize optical node resources, such as transponders, multiplexers and wavelength selective switches, needed to provide and maintain high quality of network services, in ultra-wideband wavelength division multiplexed networks, at low cost. A model based on integer programming is proposed, which includes a detailed description of optical network nodal resources. The developed optimization tools are used to study the ultra-wideband wavelength division multiplexed network performance when compared with the traditional C-band wavelength division multiplexed networks. The analysis is carried out for realistic networks of different dimensions and traffic demand sets.
New generation of optical nodes in dense wavelength division multiplexed networks enables operators to improve service flexibility and make significant savings, both in operational and capital expenditures. Thus the main objective of the study is to minimize optical node resources, such as transponders, multiplexers and wavelength selective switches, needed to provide and maintain high quality dense wavelength division multiplexed network services using new generation of optical nodes. A model based on integer programming is proposed, which includes a detailed description of an optical network node. The impact on the network performance of conventional reconfigurable optical add drop multiplexer technology is compared with colorless, directionless and contentionless approaches. The main focus of the presented study is the analysis of the network congestion problem arising in the context of both reconfigurable optical add drop multiplexer technologies. The analysis is supported by results of numerical experiments carried out for realistic networks of different dimensions and traffic demand sets.
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