Service Composition and Customization of Its Features based on Combined Classification

Majlesi Journal of Electrical Engineering

مقاله 7، دوره 13، شماره 4، اسفند 2019، صفحه 73-80   

نوع مقاله: Review Article

نویسندگان

Mohsen Eghbali¹؛ Sima Emadi^{* 2}

¹1- Department of Computer Science, Yazd Science and Research Branch, Islamic Azad University, Yazd, Iran

²Department of Computer Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran

چکیده

By promoting service-oriented architecture in e-services of organizations and inter-organizational relationships, service quality is more focused. To provide high quality combined service, it is necessary to identify quality requirements of users and offer service in line with those. Service users tend to choose a combined service among the huge collection of available services based on quality of service. In the case of competition among rivals, service providers must customize features of service as one of the key strategies. Customization involves the combination of service features based on user requests, these strategies raise new problems on the expression and dissemination of quality information, service identification and setting qualitative offers to service users. In the previous methods, pre-processing step was not performed in the services set, and false service suggestions to the user were possible.  In this study, nearest neighbor algorithm was offered to identify consumers and customize their quality of service. Also, Isodata has been used to cluster and filter the services. At the end, a case study was presented to illustrate the proposed method. The results of the evaluation show that the proposed method has tried to solve the existing shortcomings.

کلیدواژه‌ها

Service Selection؛ Access Control Based on the Features؛ Service Quality Model؛ Customization of Services Features؛ Service composition؛ Web Services؛ Clustering؛ Optimization؛ Isodata Clustering؛ k-Means Algorithm

مراجع

[1] Soltan aghaie, M., & Khatibi, N., (1391). “Study of different methods and compare the different approaches that combine services,” Conference on Science and Computer Engineering Islamic Azad University of Najafabad.

[2] Al-Helal, H., & Gamble, R. (2014). “Introducing replaceability into web service composition. IEEE Transactions on Services Computing,” 7(2), 198-209.

[3] Pejman, E., Rastegari, Y., Esfahani, P. M., & Salajegheh, A. (2012, March). “Web service composition methods: A survey.” In Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol. 1).

[4] Wu, J., Chen, L., & Liang, T. (2014). “Selecting dynamic skyline services for QoS-based service composition. Applied Mathematics & Information Sciences,” 8(5), 2579.

[5] Bock, D. E., Mangus, S. M., & Folse, J. A. G. (2016). “The road to customer loyalty paved with service customization.” Journal of Business Research, vol 69(10), 3923-3932.

[6] Yan, J., Gao, H., & Mu, Y. (2014, November). “Attribute Based Service Customization and Selection. ” In 2014 IEEE 7th International Conference on Service-Oriented Computing and Applications (pp. 57-64). IEEE.

[7] Memarsadeghi, N., Mount, D. M., Netanyahu, N. S., & Le Moigne, J. (2007). A fast implementation of the ISODATA clustering algorithm. ” International Journal of Computational Geometry & Applications, 17(01), 71-103.

[8] Zhang, W., Chang, C. K., Feng, T., & Jiang, H. Y. (2010, July). QoS-based dynamic web service composition with ant colony optimization. ” In 2010 IEEE 34th Annual Computer Software and Applications Conference (pp. 493-502). IEEE.

[9] Shen, Y., Yang, X., Wang, Y., & Ye, Z. (2012, June). Optimizing QoS-aware services composition for concurrent processes in dynamic resource-constrained environments. In Web Services (ICWS),” 2012 IEEE 19th International Conference on (pp. 250-258). IEEE

[10] Zhang, G. (2014, November). Selection of QoS Support on Artificial Immune Network Classifier for Dynamic Web Service Composition. In Computational Intelligence and Security (CIS),” 2014 Tenth International Conference on (pp. 643-646). IEEE.

[11] Benouaret, K., Benslimane, D., Hadjali, A., & Barhamgi, M. (2011, July). Top-k web service compositions using fuzzy dominance relationship. In Services Computing (SCC),” 2011 IEEE International Conference on (pp. 144-151). IEEE.

[12] Deng, S., Huang, L., Tan, W., & Wu, Z. (2014). Top-automatic service composition: A parallel method for large-scale service sets.” IEEE Transactions on Automation Science and Engineering, 11(3), 891-905.

[13] Alrifai, M., Skoutas, D., & Risse, T. (2010, April). Selecting skyline services for QoS-based web service composition. ” In Proceedings of the 19th international conference on World Wide Web (pp. 11-20). ACM.

[14] Memarsadeghi, N., Mount, D. M., Netanyahu, N. S., & Le Moigne, J. (2007). A fast implementation of the ISODATA clustering algorithm. ” International Journal of Computational Geometry & Applications, 17(01), 71-103.