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Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices

With the development of the information age, the importance of edge computing has been highlighted in industrial site monitoring, health management, and fault diagnosis. Among them, the processing and computing of signals in edge scenarios is the cornerstone of realizing these scenarios. While the p...

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Detalles Bibliográficos
Autores principales: Song, Ping, Qie, Youtian, Hao, Chuangbo, Li, Yifan, Zhao, Yue, Hao, Yi, Liu, Hongbo, Qi, Yishen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371039/
https://www.ncbi.nlm.nih.gov/pubmed/35957278
http://dx.doi.org/10.3390/s22155720
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author Song, Ping
Qie, Youtian
Hao, Chuangbo
Li, Yifan
Zhao, Yue
Hao, Yi
Liu, Hongbo
Qi, Yishen
author_facet Song, Ping
Qie, Youtian
Hao, Chuangbo
Li, Yifan
Zhao, Yue
Hao, Yi
Liu, Hongbo
Qi, Yishen
author_sort Song, Ping
collection PubMed
description With the development of the information age, the importance of edge computing has been highlighted in industrial site monitoring, health management, and fault diagnosis. Among them, the processing and computing of signals in edge scenarios is the cornerstone of realizing these scenarios. While the performance of edge devices has been dramatically improved, the demand for signal processing in the edge side has also ushered in explosive growth. However, the deployment of traditional serial or parallel signal processing architectures on edge devices has problems such as poor flexibility, low efficiency, and low resource utilization, making edge devices unable to exert their maximum performance. Therefore, this paper proposes a resource-saving customizable pipeline network architecture with a space-optimized resource allocation method and a coordinate addressing method for irregular topology. This architecture significantly improves the flexibility of multi-signal processing in edge devices, improves resource utilization, and further increases the performance potential of edge devices. Finally, we designed a comparative experiment to prove that the resource-saving and customizable pipeline network architecture can significantly reduce resource consumption under the premise of meeting real-time processing requirements.
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spelling pubmed-93710392022-08-12 Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices Song, Ping Qie, Youtian Hao, Chuangbo Li, Yifan Zhao, Yue Hao, Yi Liu, Hongbo Qi, Yishen Sensors (Basel) Article With the development of the information age, the importance of edge computing has been highlighted in industrial site monitoring, health management, and fault diagnosis. Among them, the processing and computing of signals in edge scenarios is the cornerstone of realizing these scenarios. While the performance of edge devices has been dramatically improved, the demand for signal processing in the edge side has also ushered in explosive growth. However, the deployment of traditional serial or parallel signal processing architectures on edge devices has problems such as poor flexibility, low efficiency, and low resource utilization, making edge devices unable to exert their maximum performance. Therefore, this paper proposes a resource-saving customizable pipeline network architecture with a space-optimized resource allocation method and a coordinate addressing method for irregular topology. This architecture significantly improves the flexibility of multi-signal processing in edge devices, improves resource utilization, and further increases the performance potential of edge devices. Finally, we designed a comparative experiment to prove that the resource-saving and customizable pipeline network architecture can significantly reduce resource consumption under the premise of meeting real-time processing requirements. MDPI 2022-07-30 /pmc/articles/PMC9371039/ /pubmed/35957278 http://dx.doi.org/10.3390/s22155720 Text en © 2022 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
Song, Ping
Qie, Youtian
Hao, Chuangbo
Li, Yifan
Zhao, Yue
Hao, Yi
Liu, Hongbo
Qi, Yishen
Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices
title Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices
title_full Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices
title_fullStr Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices
title_full_unstemmed Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices
title_short Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices
title_sort resource-saving customizable pipeline network architecture for multi-signal processing in edge devices
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371039/
https://www.ncbi.nlm.nih.gov/pubmed/35957278
http://dx.doi.org/10.3390/s22155720
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