Fernando Jurado-Lasso
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F. Fernando Jurado-Lasso
Engineer specializing in IoT, Networked Embedded Systems, and Machine Learning for communications and networking
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  • IEEE Access
  • Volume 10
  • Pages 23560-23592
  • March 2022
A survey on machine learning software-defined wireless sensor networks (ML-SDWSNS): Current status and major challenges
Authors
Affiliations

F. F. Jurado-Lasso

The University of Melbourne

Technical University of Denmark

L. Marchegiani

Aalborg University

J. F. Jurado

Universidad Nacional de Colombia

A. M. Abu-Mahfouz

University of Johannesburg

Council for Scientific and Industrial Research

X. Fafoutis

Technical University of Denmark

Published

March 2022

Doi

10.1109/ACCESS.2022.3153521

Links

DOI

PDF

Abstract
Wireless Sensor Network (WSN), which are enablers of the Internet of Things (IoT) technology, are typically used en-masse in widely physically distributed applications to monitor the dynamic conditions of the environment. They collect raw sensor data that is processed centralised. With the current traditional techniques of state-of-art WSN programmed for specific tasks, it is hard to react to any dynamic change in the conditions of the environment beyond the scope of the intended task. To solve this problem, a synergy between Software-Defined Networking (SDN) and WSN has been proposed. This paper aims to present the current status of Software-Defined Wireless Sensor Network (SDWSN) proposals and introduce the readers to the emerging research topic that combines Machine Learning (ML) and SDWSN concepts, also called ML-SDWSNs. ML-SDWSN grants an intelligent, centralised and resource-aware …
BibTeX citation
                        @article{JuradoFafoutis2022,
author = {Jurado Lasso, Fabian Fernando and Marchegiani, Letizia and
Jurado, Jesus Fabian and Abu-Mahfouz, Adnan M. and Fafoutis,
Xenofon},
title = {A Survey on Machine Learning Software-Defined Wireless Sensor
Networks {(ML-SDWSNS):} {Current} Status and Major Challenges},
journal = {IEEE Access},
volume = {10},
pages = {23560-23592},
date = {2022-03},
doi = {10.1109/ACCESS.2022.3153521}
}
License
CC BY
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A survey on machine learning software-defined wireless sensor networks (ML-SDWSNS): Current status and major challenges
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