Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm
The number of services on the internet has experienced explosive growth, and the rapid and accurate discovery of required services among a vast array of similarly functioning services with differing degrees of quality has become a critical and challenging aspect of service computing. In this paper,...
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MDPI AG
2025-04-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/9/1402 |
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| author | Zhengwang Ye Hehe Sheng Haiyang Zou |
| author_facet | Zhengwang Ye Hehe Sheng Haiyang Zou |
| author_sort | Zhengwang Ye |
| collection | DOAJ |
| description | The number of services on the internet has experienced explosive growth, and the rapid and accurate discovery of required services among a vast array of similarly functioning services with differing degrees of quality has become a critical and challenging aspect of service computing. In this paper, we propose a trusted service discovery algorithm based on an ant colony system (TSDA-ACS). The algorithm integrates a credibility-based trust model with the ant colony search algorithm to facilitate the discovery of trusted web services. During the evaluation process, the trust model employs a pseudo-stochastic proportion to select nodes, where nodes with higher reputation have a greater probability of being chosen. The ant colony uses a voting method to calculate the credibility of service nodes, factoring in both credibility and non-credibility from the query node’s perspective. The algorithm employs an information acquisition strategy, a trust information merging strategy, a routing strategy, and a random wave strategy to guide ant search. To evaluate the effectiveness of the TSDA-ACS, this paper introduces the random walk search algorithm (RW), the classic max–min ant colony algorithm (MMAS), and a trustworthy service discovery based on a modified ant colony algorithm (TSDMACS) for comparison with the TSDA-ACS algorithm. The experiments demonstrate that this method can achieve the discovery of trusted web services with high recall and precision rates. Finally, the efficacy of the proposed algorithm is validated through comparison experiments across various network environments. |
| format | Article |
| id | doaj-art-e3bb130be803422a98165193d3616427 |
| institution | OA Journals |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-e3bb130be803422a98165193d36164272025-08-20T02:24:48ZengMDPI AGMathematics2227-73902025-04-01139140210.3390/math13091402Trusted Web Service Discovery Based on a Swarm Intelligence AlgorithmZhengwang Ye0Hehe Sheng1Haiyang Zou2School of Computer Science, Tonghua Normal University, Tonghua 134002, ChinaBeijing Huawei Digital Technology Co., Ltd., Beijing 100077, ChinaSchool of Computer Science, China West Normal University, Nanchong 637009, ChinaThe number of services on the internet has experienced explosive growth, and the rapid and accurate discovery of required services among a vast array of similarly functioning services with differing degrees of quality has become a critical and challenging aspect of service computing. In this paper, we propose a trusted service discovery algorithm based on an ant colony system (TSDA-ACS). The algorithm integrates a credibility-based trust model with the ant colony search algorithm to facilitate the discovery of trusted web services. During the evaluation process, the trust model employs a pseudo-stochastic proportion to select nodes, where nodes with higher reputation have a greater probability of being chosen. The ant colony uses a voting method to calculate the credibility of service nodes, factoring in both credibility and non-credibility from the query node’s perspective. The algorithm employs an information acquisition strategy, a trust information merging strategy, a routing strategy, and a random wave strategy to guide ant search. To evaluate the effectiveness of the TSDA-ACS, this paper introduces the random walk search algorithm (RW), the classic max–min ant colony algorithm (MMAS), and a trustworthy service discovery based on a modified ant colony algorithm (TSDMACS) for comparison with the TSDA-ACS algorithm. The experiments demonstrate that this method can achieve the discovery of trusted web services with high recall and precision rates. Finally, the efficacy of the proposed algorithm is validated through comparison experiments across various network environments.https://www.mdpi.com/2227-7390/13/9/1402service-oriented computingweb service discoverytrust modelP2Pant colony |
| spellingShingle | Zhengwang Ye Hehe Sheng Haiyang Zou Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm Mathematics service-oriented computing web service discovery trust model P2P ant colony |
| title | Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm |
| title_full | Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm |
| title_fullStr | Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm |
| title_full_unstemmed | Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm |
| title_short | Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm |
| title_sort | trusted web service discovery based on a swarm intelligence algorithm |
| topic | service-oriented computing web service discovery trust model P2P ant colony |
| url | https://www.mdpi.com/2227-7390/13/9/1402 |
| work_keys_str_mv | AT zhengwangye trustedwebservicediscoverybasedonaswarmintelligencealgorithm AT hehesheng trustedwebservicediscoverybasedonaswarmintelligencealgorithm AT haiyangzou trustedwebservicediscoverybasedonaswarmintelligencealgorithm |