A service composition model based on user experience in Ubi-cloud comp
The ubiquitous cloud computing environment supports software as service that allows for an efficient usage by the developer, user, and manager. But within ubiquitous cloud computing, numerous services are being provided by various service providers, making it difficult for the developer to find the service needed for system development or to apply and adopt it during development. In this paper, we propose a service composition model based on user experience where the user can find the type of service that he needs, construct a composition and apply it to the overall system development. The proposed model has three factors: service characteristics, personal information, and user preference. The service characteristics to apply the most appropriate service that the user intends to apply was taken into consideration, personal information that takes into account individual characteristics of the user and a user preference that takes into account the preferred parts in the field that the user seeks to develop was applied. To evaluate the suggested method, 100 people were recruited and surveyed on user satisfaction. The result shows that the proposed method performed better than the existing methods.
KeywordsUser experience Ubiquitous cloud computing SaaS Service based application Service composition
- 2.Tsai, Joseph C., & Yen, Neil Y. (2013). Cloud-empowered multimedia service: An automatic video storytelling tool. Journal of Convergence, 4(3), 13–19.Google Scholar
- 3.Kim, Jungsun Sunny, Byun, Jeuongwoo, & Jeong, Hwayoung. (2013). Cloud AEHS: Advanced learning system using user preferences. Journal of Convergence, 4(3), 31–36.Google Scholar
- 4.Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., et al. (2010). A view of cloud computing. Communications of the ACM, 53, 50–58.Google Scholar
- 6.Zhao, Y., Raicu, I., & Lu, S. (2008). Cloud computing and grid computing 360-degree compared grid computing environments workshop. New York: GCE ’08.Google Scholar
- 7.Sadashiv, N. & Kumar, S.M.D. (2011). Cluster, grid and cloud computing: A detailed comparison The 6th International Conference on Computer Science & Education (ICCSE 2011) (pp. 477–482), August 3–5. Singapore: SuperStar Virgo.Google Scholar
- 10.Kwon, J., Park, K., Lee, D., & Lee, S. (2007). PSR: Pre-computing solutionsin RDBMS for fast web, service composition search. New York: ICWS.Google Scholar
- 11.Utkarsh, S., Kamesh, M., Jennifer, W., & Rajeev, M. (2006). Query optimization over web services. In: VLDB ’06 Proceedings of the 32nd International Conference on Very large data bases (pp. 355–366.Google Scholar
- 14.International Organization for Standardization. (2010). Ergonomics of human system interaction-Part 210: Human-centered design for interactive systems. ISO 9241–210, 2010. http://www.iso.org/iso/catalogue_detail.htm?csnumber=52075.
- 15.Morville, P. (2005). Ambient findability: What we find changes who we become. Sebastopol: O’Reilly Media, Inc.Google Scholar