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Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks

Wireless sensor networks have been attracting research attention for the past decade and will continue to be a hot topic due to the emerging trend of Internet-of-Things (IoT). Edge computing for IoT (Edge-IoT) is a promising framework that can help low-powered sensor networks to conduct complex comp...

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Detalles Bibliográficos
Autores principales: Xu, Zhirong, Cai, Ming, Li, Xiaoyan, Hu, Tianlei, Song, Qianshu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539615/
https://www.ncbi.nlm.nih.gov/pubmed/31060264
http://dx.doi.org/10.3390/s19092078
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author Xu, Zhirong
Cai, Ming
Li, Xiaoyan
Hu, Tianlei
Song, Qianshu
author_facet Xu, Zhirong
Cai, Ming
Li, Xiaoyan
Hu, Tianlei
Song, Qianshu
author_sort Xu, Zhirong
collection PubMed
description Wireless sensor networks have been attracting research attention for the past decade and will continue to be a hot topic due to the emerging trend of Internet-of-Things (IoT). Edge computing for IoT (Edge-IoT) is a promising framework that can help low-powered sensor networks to conduct complex computational tasks. Different from the existing works that focus on cooperative task execution for edge and sensor networks, in this paper, we investigate the problem of reliable data transmission in edge-aided sensor networks. Firstly, we discuss how edge servers can help to improve the data transmission of sensor networks. Secondly, we propose a forwarding scheme for edge nodes to forward packets according to coverage and corresponding interference. Thirdly, we propose an edge-based error recovery approach. By employing edge servers for data transmission and error recovery, the efficiency and reliability of data transmissions can be largely improved.
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spelling pubmed-65396152019-06-04 Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks Xu, Zhirong Cai, Ming Li, Xiaoyan Hu, Tianlei Song, Qianshu Sensors (Basel) Article Wireless sensor networks have been attracting research attention for the past decade and will continue to be a hot topic due to the emerging trend of Internet-of-Things (IoT). Edge computing for IoT (Edge-IoT) is a promising framework that can help low-powered sensor networks to conduct complex computational tasks. Different from the existing works that focus on cooperative task execution for edge and sensor networks, in this paper, we investigate the problem of reliable data transmission in edge-aided sensor networks. Firstly, we discuss how edge servers can help to improve the data transmission of sensor networks. Secondly, we propose a forwarding scheme for edge nodes to forward packets according to coverage and corresponding interference. Thirdly, we propose an edge-based error recovery approach. By employing edge servers for data transmission and error recovery, the efficiency and reliability of data transmissions can be largely improved. MDPI 2019-05-05 /pmc/articles/PMC6539615/ /pubmed/31060264 http://dx.doi.org/10.3390/s19092078 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Zhirong
Cai, Ming
Li, Xiaoyan
Hu, Tianlei
Song, Qianshu
Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks
title Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks
title_full Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks
title_fullStr Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks
title_full_unstemmed Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks
title_short Edge-Aided Reliable Data Transmission for Heterogeneous Edge-IoT Sensor Networks
title_sort edge-aided reliable data transmission for heterogeneous edge-iot sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539615/
https://www.ncbi.nlm.nih.gov/pubmed/31060264
http://dx.doi.org/10.3390/s19092078
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