Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty Environments
Social networks (SNs) and many other industrial types of networks, structured by many nodes and relationships between nodes, have become an integral part of our daily lives. A binary-state network (BN) is often used to model structures and applications of SNs and other networks. The BN reliability i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/19/9514 |
| _version_ | 1797480819104677888 |
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| author | Wei-Chang Yeh Wenbo Zhu Chia-Ling Huang |
| author_facet | Wei-Chang Yeh Wenbo Zhu Chia-Ling Huang |
| author_sort | Wei-Chang Yeh |
| collection | DOAJ |
| description | Social networks (SNs) and many other industrial types of networks, structured by many nodes and relationships between nodes, have become an integral part of our daily lives. A binary-state network (BN) is often used to model structures and applications of SNs and other networks. The BN reliability is the probability that a BN functions continuously, i.e., that there is always a path between a specific pair of nodes. This metric is a popular index for designing, managing, controlling, and evaluating networks. The traditional BN reliability assumes that the network is activity-on-arc, and the reliability of each arc is known in advance. However, this is not always the case. Functioning components operate in different environments; moreover, a network might have newly installed components. Hence, the reliability of these components is not always known. To resolve the aforementioned problems, in which the reliability of some components of a network is uncertain, we introduce the fuzzy concept for the analysis of these components and propose a new algorithm to solve this uncertainty-component activity-on-node BN reliability problem. The time complexity of the proposed algorithm is analyzed, and the superior performance of the algorithm is demonstrated through examples. |
| first_indexed | 2024-03-09T22:06:37Z |
| format | Article |
| id | doaj.art-776fd60bef0a4913a945c0467ee61d40 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T22:06:37Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-776fd60bef0a4913a945c0467ee61d402023-11-23T19:40:53ZengMDPI AGApplied Sciences2076-34172022-09-011219951410.3390/app12199514Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty EnvironmentsWei-Chang Yeh0Wenbo Zhu1Chia-Ling Huang2Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 300044, TaiwanSchool of Mechatronical Engineering and Automation, Foshan University, Foshan 528000, ChinaDepartment of International Logistics and Transportation Management, Kainan University, Taoyuan 33857, TaiwanSocial networks (SNs) and many other industrial types of networks, structured by many nodes and relationships between nodes, have become an integral part of our daily lives. A binary-state network (BN) is often used to model structures and applications of SNs and other networks. The BN reliability is the probability that a BN functions continuously, i.e., that there is always a path between a specific pair of nodes. This metric is a popular index for designing, managing, controlling, and evaluating networks. The traditional BN reliability assumes that the network is activity-on-arc, and the reliability of each arc is known in advance. However, this is not always the case. Functioning components operate in different environments; moreover, a network might have newly installed components. Hence, the reliability of these components is not always known. To resolve the aforementioned problems, in which the reliability of some components of a network is uncertain, we introduce the fuzzy concept for the analysis of these components and propose a new algorithm to solve this uncertainty-component activity-on-node BN reliability problem. The time complexity of the proposed algorithm is analyzed, and the superior performance of the algorithm is demonstrated through examples.https://www.mdpi.com/2076-3417/12/19/9514social networks (SNs)binary-state network (BN)network reliabilityuncertainty environmentsactivity-on-nodebinary-addition-tree algorithm (BAT) |
| spellingShingle | Wei-Chang Yeh Wenbo Zhu Chia-Ling Huang Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty Environments Applied Sciences social networks (SNs) binary-state network (BN) network reliability uncertainty environments activity-on-node binary-addition-tree algorithm (BAT) |
| title | Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty Environments |
| title_full | Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty Environments |
| title_fullStr | Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty Environments |
| title_full_unstemmed | Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty Environments |
| title_short | Reliability of Social Networks on Activity-on-Node Binary-State with Uncertainty Environments |
| title_sort | reliability of social networks on activity on node binary state with uncertainty environments |
| topic | social networks (SNs) binary-state network (BN) network reliability uncertainty environments activity-on-node binary-addition-tree algorithm (BAT) |
| url | https://www.mdpi.com/2076-3417/12/19/9514 |
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