Abstract
The number of services is proliferating dramatically and the rate of services’ evolution has also been increasingly fluctuating in recent years. The demands of service composition also show the characteristics of individuation and diversification at the same time. The traditional methods of service composition are difficult to meet the multiple granularity demands of users. This paper proposes a novel multiple granular service composition model based on services granular space. The model firstly constructs service granularity by service clustering. And then constructs the service granularity space according to the relationships between service granularities. So the process of getting appropriate service compositions can be transformed into getting service compositions from different granularity layers. Through experimental analysis, we can demonstrate that this model can provide users with different granularity service compositions which meet the multiple granularity demands of users. And can also decrease the response time of service composition at the same time.
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Acknowledgments
This work was partially supported by the National Natural Science Foundation of China (Nos. 61602536, 61309029 and 61273293), the Fundamental Research Funds for the Central Universities, and the Discipline Construction Foundation of the Central University of Finance and Economics.
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Zhang, Y., Qiao, Y., Liu, Z., Geng, X., Jia, H. (2016). A Novel Multi-granularity Service Composition Model. In: Wang, G., Han, Y., Martínez Pérez, G. (eds) Advances in Services Computing. APSCC 2016. Lecture Notes in Computer Science(), vol 10065. Springer, Cham. https://doi.org/10.1007/978-3-319-49178-3_3
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DOI: https://doi.org/10.1007/978-3-319-49178-3_3
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