Dr. Stanisław Kozdrowski Profile

Dr. Stanisław Kozdrowski

at Warsaw Univ of Technology

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Publications (3)

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Proceedings Article | 6 November 2019 Paper

Application of evolutionary algorithms to DWDM optical networks design

Stanisław Kozdrowski, Rafał Biedrzycki

Proceedings Volume 11176, 111760B (2019) https://doi.org/10.1117/12.2536666

KEYWORDS: Polishing, Computer programming, Network architectures

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The subject of the study is an application of evolutionary algorithms to optical node optimization in dense wavelength division multiplexing optical networks. The wider context of the presented research is in essence an improvement of service flexibility and achieving savings in capital expenditures in DWDM networks. Thus, the main objective of the optimization is to minimize capital expenditure, which includes the costs of optical node resources, such as transponders and filters used in new generation of reconfigurable optical add drop multiplexers, etc. For this purpose a model based on integer programming is proposed. The efficiency of the integer programming based software is compared with that of evolutionary algorithms. The results obtained show that there is a large advantage in using evolutionary algorithms for optimizing large optical networks when compared with integer programming and mixed integer programming, whereby the two latter algorithms fail to find the optimal solution within reasonable computational time. The numerical experiments were carried out for realistic networks of different dimensions and traffic demand sets.

Proceedings Article | 13 September 2019 Paper

Application of evolutionary algorithm to optimization of DWDM networks

Kacper Wnuk, Arkadiusz Sikorski, Sławomir Sujecki, Stanisław Kozdrowski

Proceedings Volume 11204, 112040D (2019) https://doi.org/10.1117/12.2536756

KEYWORDS: Computer programming, Electronics

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The subject of the study is an application of Integer Programming method and Evolutionary Algorithm to optical Dense Wavelength Division Multiplexing network optimization. The main objective of the optimization is to minimize capital expenditure, which includes the costs of optical node resources, such as transponders and filters used in New Generation of Reconfigurable Optical Add Drop Multiplexers. For this purpose a model based on Integer Programming is proposed. The efficiency of the Integer Programming based software is compared with that of Evolutionary Algorithm. The results obtained show that there is an advantage in using EA for optimizing a large optical network when compared with Integer Programming. A realistic network of large dimension and traffic demand set was used in the numerical experiments.

Proceedings Article | 13 September 2019 Paper

Application of machine learning methods in provisioning of DWDM channels

Piotr Paziewski, Sławomir Sujecki, Stanisław Kozdrowski

Proceedings Volume 11204, 1120407 (2019) https://doi.org/10.1117/12.2536656

KEYWORDS: Networks, Neurons, Polishing, Data modeling

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Complexity and size of modern optic-fiber networks start to challenge the traditional methods of managing them and yet majority of telecommunication companies still report rapid growth of their optical networks. One of essential problems in managing optic-fiber networks is calculating the Quality of Transmission (QoT) of given path in network. The unit responsible for this task is Optical Performance Unit (OPU) which communicates with Network Management System (NMS). OPU's task is to determine whether it is possible to transmit signal through a given path. Modern OPUs are still operating based on traditional algorithms e.g. these systems take into consideration known physics rules and information about the network parameters, calculating transmission losses for each path. Main parameter that determines the OPUs result is Optical Signal to Noise Ratio (OSNR). However, measuring its value from NMS level is often not practical. An alternative solution to this problem might prove the application of Machine Learning (ML) algorithms for the estimation of OSNR. In this contribution an application of Artificial Neural Network (ANN) to an evaluation of OSNR in an optical Dense Wavelength Division Multiplexing (DWDM) network is investigated.

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