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 Systems Journal
  • Volume 18
  • Pages 1068-1079
  • June 2024
ELISE: A Reinforcement Learning Framework to Optimize the Slotframe Size of the TSCH Protocol in IoT Networks
Authors
Affiliations

F. F. Jurado-Lasso

Technical University of Denmark

M. Barzegaran

University of California, Irvine

J. F. Jurado

Universidad Nacional de Colombia

X. Fafoutis

Technical University of Denmark

Published

June 2024

Doi

10.1109/JSYST.2024.3371429

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Abstract
The Internet of Things is shaping the next generation of cyber–physical systems to improve the future industry for smart cities. It has created novel and essential applications that require specific network performance to enhance the quality of services. Since network performance requirements are application-oriented, it is of paramount importance to provide tailored solutions that seamlessly manage the network resources and orchestrate the network to satisfy user requirements. In this article, we propose ELISE, a reinforcement learning (RL) framework to optimize the slotframe size of the time slotted channel hopping protocol in IIoT networks while considering the user requirements. We primarily address the problem of designing a framework that self-adapts to the optimal slotframe length that best suits the user’s requirements. The framework takes care of all functionalities involved in the correct functioning of the …
BibTeX citation
                        @article{JuradoFafoutis2024,
author = {Jurado Lasso, Fabian Fernando and Barzegaran, Mohammadreza
and Jurado, Jesus Fabian and Fafoutis, Xenofon},
title = {ELISE: {A} {Reinforcement} {Learning} {Framework} to
{Optimize} the {Slotframe} {Size} of the {TSCH} {Protocol} in {IoT}
{Networks}},
journal = {IEEE Systems Journal},
volume = {18},
number = {2},
pages = {1068-1079},
date = {2024-06},
doi = {10.1109/JSYST.2024.3371429}
}
License
CC BY
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ELISE: A Reinforcement Learning Framework to Optimize the Slotframe Size of the TSCH Protocol in IoT Networks
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ORCID 0000-0002-5005-781X PGP public key   Fingerprint:
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