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An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing

Satellite edge computing has attracted the attention of many scholars due to its extensive coverage and low delay. Satellite edge computing research remains focused on on-orbit task scheduling. However, existing research has not considered the situation where heavily loaded satellites cannot partici...

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Detalles Bibliográficos
Autores principales: Hu, Yifei, Gong, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181455/
https://www.ncbi.nlm.nih.gov/pubmed/37177476
http://dx.doi.org/10.3390/s23094271
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author Hu, Yifei
Gong, Wenbin
author_facet Hu, Yifei
Gong, Wenbin
author_sort Hu, Yifei
collection PubMed
description Satellite edge computing has attracted the attention of many scholars due to its extensive coverage and low delay. Satellite edge computing research remains focused on on-orbit task scheduling. However, existing research has not considered the situation where heavily loaded satellites cannot participate in offloading. To solve this problem, this study first models the task scheduling of dynamic satellite networks as a minimization problem that considers both the weighted delay and energy consumption. In addition, a hybrid genetic binary particle swarm optimization (GABPSO) algorithm is proposed to solve this optimization problem. The simulation results demonstrate that the proposed method outperforms the other three baseline algorithms.
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spelling pubmed-101814552023-05-13 An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing Hu, Yifei Gong, Wenbin Sensors (Basel) Article Satellite edge computing has attracted the attention of many scholars due to its extensive coverage and low delay. Satellite edge computing research remains focused on on-orbit task scheduling. However, existing research has not considered the situation where heavily loaded satellites cannot participate in offloading. To solve this problem, this study first models the task scheduling of dynamic satellite networks as a minimization problem that considers both the weighted delay and energy consumption. In addition, a hybrid genetic binary particle swarm optimization (GABPSO) algorithm is proposed to solve this optimization problem. The simulation results demonstrate that the proposed method outperforms the other three baseline algorithms. MDPI 2023-04-25 /pmc/articles/PMC10181455/ /pubmed/37177476 http://dx.doi.org/10.3390/s23094271 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hu, Yifei
Gong, Wenbin
An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing
title An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing
title_full An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing
title_fullStr An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing
title_full_unstemmed An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing
title_short An On-Orbit Task-Offloading Strategy Based on Satellite Edge Computing
title_sort on-orbit task-offloading strategy based on satellite edge computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181455/
https://www.ncbi.nlm.nih.gov/pubmed/37177476
http://dx.doi.org/10.3390/s23094271
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