Service Combination Using Lagrange Optimization Method and Evolutionary Algorithm
Various methods on the combination of web services have been implemented in the past. Each one of these methods is aimed at achieving an optimal service combination among the numerous ones; however, each method suffered from some disadvantages, regardless of its advantages. The selection of a suitable approach is key to adopting an optimal web service combination. The present study tackles the investigation of the Lagrange optimization method, which is a systematic approach based on the minimum distance between the user’s request and the Lagrange curve. The results obtained from using the Lagrange optimization method indicated that this method provides a yielding output compared to other methods of web service combination. Also, given the features of Lagrange functions, it can be concluded that the Lagrange method can be used for higher service quality modes and settle multi-objective problems, while this might be unrealized in other related methods. Finally, the evolutionary algorithm of Single_EA (Single Evolutionary Algorithm) was used to implement the plan.
Griffiths, N., & Chao, K. M. (2010). Agent-based service-oriented computing (Vol. 1). Springer.
Zhang, C. (2011, March). Adaptive genetic algorithm for QoS-aware service selection. In Advanced Information Networking and Applications (WAINA), 2011 IEEE Workshops of International Conference on (pp. 273-278). IEEE.
Zhao, L., Ren, Y., Li, M., & Sakurai, K. (2012). Flexible service selection with user-specific QoS support in service-oriented architecture. Journal of Network and Computer Applications, 35(3), 962-973.
Wang, H., Tong, P., Thompson, P., & Li, Y. (2007, October). QoS-based web services selection. In e-Business Engineering, 2007. ICEBE 2007. IEEE International Conference on (pp. 631-637). IEEE.
Sathya,M.,Swarnamugi,M.,Dhavachelvan,P.,& Sureshkumar, G. (2010). Evaluation of qos based web-service selection techniques for service composition. International Journal of Software Engineering, 1(5), 73-90.
Zhao, X., Shen, L., Peng, X., & Zhao, W. (2015). Toward SLA-constrained service composition: An approach based on a fuzzy linguistic preference model and an evolutionary algorithm. Information Sciences, 316, 370-396.
Funaro, D. (2008). Polynomial approximation of differential equations (Vol. 8). Springer Science & Business Media.
Lin, Z., Chen, M., & Ma, Y. (2010). The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. arXiv preprint arXiv:1009.5055.
Fletcher, R. (2013). Practical methods of optimization. John Wiley & Sons.
Zeidler, E. (2013). Nonlinear Functional Analysis and Its Applications: III: Variational Methods and Optimization . Springer Science & Business Media.
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