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A Survey on Software-Defined Wireless Sensor Networks: Current status, machine learning approaches and major challenges
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  • Fabian Fernando Jurado Lasso ,
  • Letizia Marchegiani ,
  • Jesus Fabian Jurado ,
  • Adnan Abu Mahfouz ,
  • Xenofon Fafoutis
Fabian Fernando Jurado Lasso
Technical University of Denmark, Technical University of Denmark, Technical University of Denmark

Corresponding Author:[email protected]

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Letizia Marchegiani
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Jesus Fabian Jurado
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Adnan Abu Mahfouz
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Xenofon Fafoutis
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This paper is aimed to present a comprehensive survey of relevant research over the period 2012-2021 of Software-Defined Wireless Sensor Network (SDWSN) proposals and Machine Learning (ML) techniques to perform network management, policy enforcement, and network configuration functions. This survey provides helpful information and insights to the scientific and industrial communities, and professional organisations interested in SDWSNs, mainly the current state-of-art, machine learning techniques, and open issues.
2022Published in IEEE Access volume 10 on pages 23560-23592. 10.1109/ACCESS.2022.3153521