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Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing
The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBES...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280632/ https://www.ncbi.nlm.nih.gov/pubmed/37346574 http://dx.doi.org/10.7717/peerj-cs.1407 |
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author | Dong, Qingxia Chen, Nana Wang, Shuai |
author_facet | Dong, Qingxia Chen, Nana Wang, Shuai |
author_sort | Dong, Qingxia |
collection | PubMed |
description | The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server’s computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain’s comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing. |
format | Online Article Text |
id | pubmed-10280632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102806322023-06-21 Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing Dong, Qingxia Chen, Nana Wang, Shuai PeerJ Comput Sci Algorithms and Analysis of Algorithms The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server’s computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain’s comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing. PeerJ Inc. 2023-06-06 /pmc/articles/PMC10280632/ /pubmed/37346574 http://dx.doi.org/10.7717/peerj-cs.1407 Text en ©2023 Dong et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Dong, Qingxia Chen, Nana Wang, Shuai Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing |
title | Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing |
title_full | Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing |
title_fullStr | Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing |
title_full_unstemmed | Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing |
title_short | Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing |
title_sort | supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280632/ https://www.ncbi.nlm.nih.gov/pubmed/37346574 http://dx.doi.org/10.7717/peerj-cs.1407 |
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