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Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
Cloud manufacturing systems (CMSs) are networked, distributed and loosely coupled, so they face great uncertainty and risk. This paper combines the complex network model with multi-agent simulation in a novel approach to the robustness analysis of CMSs. Different evaluation metrics are chosen for th...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857848/ https://www.ncbi.nlm.nih.gov/pubmed/36673186 http://dx.doi.org/10.3390/e25010045 |
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author | Zheng, Xin Zhang, Xiaodong |
author_facet | Zheng, Xin Zhang, Xiaodong |
author_sort | Zheng, Xin |
collection | PubMed |
description | Cloud manufacturing systems (CMSs) are networked, distributed and loosely coupled, so they face great uncertainty and risk. This paper combines the complex network model with multi-agent simulation in a novel approach to the robustness analysis of CMSs. Different evaluation metrics are chosen for the two models, and three different robustness attack strategies are proposed. To verify the effectiveness of the proposed method, a case study is then conducted on a cloud manufacturing project of a new energy vehicle. The results show that both the structural and process-based robustness of the system are lowest under the betweenness-based failure mode, indicating that resource nodes with large betweenness are most important to the robustness of the project. Therefore, the cloud manufacturing platform should focus on monitoring and managing these resources so that they can provide stable services. Under the individual server failure mode, system robustness varies greatly depending on the failure behavior of the service provider: Among the five service providers (S1–S5) given in the experimental group, the failure of Server 1 leads to a sharp decline in robustness, while the failure of Server 2 has little impact. This indicates that the CMS can protect its robustness by identifying key servers and strengthening its supervision of them to prevent them from exiting the platform. |
format | Online Article Text |
id | pubmed-9857848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98578482023-01-21 Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation Zheng, Xin Zhang, Xiaodong Entropy (Basel) Article Cloud manufacturing systems (CMSs) are networked, distributed and loosely coupled, so they face great uncertainty and risk. This paper combines the complex network model with multi-agent simulation in a novel approach to the robustness analysis of CMSs. Different evaluation metrics are chosen for the two models, and three different robustness attack strategies are proposed. To verify the effectiveness of the proposed method, a case study is then conducted on a cloud manufacturing project of a new energy vehicle. The results show that both the structural and process-based robustness of the system are lowest under the betweenness-based failure mode, indicating that resource nodes with large betweenness are most important to the robustness of the project. Therefore, the cloud manufacturing platform should focus on monitoring and managing these resources so that they can provide stable services. Under the individual server failure mode, system robustness varies greatly depending on the failure behavior of the service provider: Among the five service providers (S1–S5) given in the experimental group, the failure of Server 1 leads to a sharp decline in robustness, while the failure of Server 2 has little impact. This indicates that the CMS can protect its robustness by identifying key servers and strengthening its supervision of them to prevent them from exiting the platform. MDPI 2022-12-27 /pmc/articles/PMC9857848/ /pubmed/36673186 http://dx.doi.org/10.3390/e25010045 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 Zheng, Xin Zhang, Xiaodong Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation |
title | Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation |
title_full | Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation |
title_fullStr | Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation |
title_full_unstemmed | Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation |
title_short | Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation |
title_sort | robustness of cloud manufacturing system based on complex network and multi-agent simulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857848/ https://www.ncbi.nlm.nih.gov/pubmed/36673186 http://dx.doi.org/10.3390/e25010045 |
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