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Impact of Machine Learning Algorithms on WDM High-Speed Optical Networks

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Proceedings of Second Doctoral Symposium on Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1374))

Abstract

This paper focuses on comparing the various machine learning (ML) algorithms that can be applicable in wavelength division multiplexing (WDM) optical networks to provide better simulation outcomes. ML, combined with WDM optical networks, helps in network control and resource management that are useful in service provisioning and resource assignment. This paper gives a comprehensive review of machine learning approaches in WDM optical networks concerning support vector machine (SVM), K-nearest neighbour (K-NN), decision tree, random forest and neural networks algorithms. These algorithms’ performances are compared in terms of accuracy and AUC; further, the accuracy and AUC results show an average outcome of 99% and 0.98, respectively. Simulation can be performed on MATLAB and Net2plan tools using different data sets in terms of average accuracy and AUC for WDM optical networks. This research’s future directions can be towards ML utilization to provide optimal routing and wavelength assignment, increasing bandwidth utilization to reduce control overheads, reduce computational complexity, security, fault occurrence and monitoring schemes for WDM optical networks supporting 5G applications.

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Author information

Authors and Affiliations

  1. Electronics and Communications Department, D.C.R.U.S.T, Murthal, Haryana, India

    Saloni Rai & Amit Kumar Garg

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  1. Saloni Rai
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  2. Amit Kumar Garg
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Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  2. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Ashish Khanna

  3. Institute of Engineering and Technology, Lucknow, Uttar Pradesh, India

    Vineet Kansal

  4. University of Calabria, Rende, Cosenza, Italy

    Giancarlo Fortino

  5. Department of Information Technology, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Rai, S., Garg, A.K. (2022). Impact of Machine Learning Algorithms on WDM High-Speed Optical Networks. In: Gupta, D., Khanna, A., Kansal, V., Fortino, G., Hassanien, A.E. (eds) Proceedings of Second Doctoral Symposium on Computational Intelligence . Advances in Intelligent Systems and Computing, vol 1374. Springer, Singapore. https://doi.org/10.1007/978-981-16-3346-1_52

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