Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks
Hybrid services use different protocols on various networks, such as WIFI networks, Bluetooth networks, 5G communications systems, and wireless sensor networks. Hybrid service compositions can be varied, representing an effective method of integrating into wireless scenarios context-aware applicatio...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-02-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718761583 |
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| _version_ | 1849691640314200064 |
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| author | Honghao Gao Kang Zhang Jianhua Yang Fangguo Wu Hongsheng Liu |
| author_facet | Honghao Gao Kang Zhang Jianhua Yang Fangguo Wu Hongsheng Liu |
| author_sort | Honghao Gao |
| collection | DOAJ |
| description | Hybrid services use different protocols on various networks, such as WIFI networks, Bluetooth networks, 5G communications systems, and wireless sensor networks. Hybrid service compositions can be varied, representing an effective method of integrating into wireless scenarios context-aware applications that can sense mobility via changes in user location and combining services to support target functions. In this article, improved particle swarm optimization is introduced into the quality service evaluation of dynamic service composition to meet the mobility requirements of hybrid networks. First, this work classifies hybrid services into different task groups to generate candidate sets and then interface matching is used to compare the operations of candidate services with user requirements to select the appropriate services. Second, the service composition is determined by the particle swarm optimization simulation process, which aims to identify an optimal plan based on the calculated value from quality of service. Third, considering a change of service repository, when the quality of a composite service is lower than a predefined threshold, the local greedy algorithm and global reconfiguration method are adopted to dynamically restructure composite services. Finally, a set of experiments is conducted to demonstrate the effectiveness of the proposed method for determining the dynamic service composition, particularly when the scale of hybrid services is large. The method provides a technical reference for engineering practice that will fulfill mobile computing needs. |
| format | Article |
| id | doaj-art-e236d7f598af409fbc5afd04602a6a5b |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2018-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-e236d7f598af409fbc5afd04602a6a5b2025-08-20T03:20:58ZengWileyInternational Journal of Distributed Sensor Networks1550-14772018-02-011410.1177/1550147718761583Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networksHonghao Gao0Kang Zhang1Jianhua Yang2Fangguo Wu3Hongsheng Liu4School of Computer Engineering and Science, Shanghai University, Shanghai, P.R. ChinaSchool of Computer Engineering and Science, Shanghai University, Shanghai, P.R. ChinaThe Sci-Tech Academy, Zhejiang University, Hangzhou, P.R. ChinaHithink RoyalFlush Information Network Co., Ltd, Hangzhou, P.R. ChinaFushun Power Supply Branch, State Grid Liaoning Electric Power Supply Co., Ltd, Fushun, P.R. ChinaHybrid services use different protocols on various networks, such as WIFI networks, Bluetooth networks, 5G communications systems, and wireless sensor networks. Hybrid service compositions can be varied, representing an effective method of integrating into wireless scenarios context-aware applications that can sense mobility via changes in user location and combining services to support target functions. In this article, improved particle swarm optimization is introduced into the quality service evaluation of dynamic service composition to meet the mobility requirements of hybrid networks. First, this work classifies hybrid services into different task groups to generate candidate sets and then interface matching is used to compare the operations of candidate services with user requirements to select the appropriate services. Second, the service composition is determined by the particle swarm optimization simulation process, which aims to identify an optimal plan based on the calculated value from quality of service. Third, considering a change of service repository, when the quality of a composite service is lower than a predefined threshold, the local greedy algorithm and global reconfiguration method are adopted to dynamically restructure composite services. Finally, a set of experiments is conducted to demonstrate the effectiveness of the proposed method for determining the dynamic service composition, particularly when the scale of hybrid services is large. The method provides a technical reference for engineering practice that will fulfill mobile computing needs.https://doi.org/10.1177/1550147718761583 |
| spellingShingle | Honghao Gao Kang Zhang Jianhua Yang Fangguo Wu Hongsheng Liu Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks International Journal of Distributed Sensor Networks |
| title | Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks |
| title_full | Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks |
| title_fullStr | Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks |
| title_full_unstemmed | Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks |
| title_short | Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks |
| title_sort | applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks |
| url | https://doi.org/10.1177/1550147718761583 |
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