Abstract
As most Web services are delivered by third parties over unreliable Internet and are late bound at run-time, it is reasonable and useful to evaluate and predict the trustworthiness of Web services. In this paper, we propose an ARIMA model-based approach to evaluate and predict Web services trustworthiness. First, we evaluate Web services trustworthiness with comprehensive trustworthy evidences collected from the Internet on a regular basis. Then, the cumulative trustworthiness evaluation records are modeled as time series. Finally, we propose an ARIMA model-based multi-step Web services trustworthiness prediction process, which can automatically and iteratively identify and optimize the model to fit the trustworthiness series data. Experiments conducted on a large-scale real-world data set show that our method can effectively evaluate and predict the trustworthiness of Web services, which helps users to reuse Web services.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Zhang, J., Zhang, L., Chung, J.: Ws-trustworthy: a framework for web services centered trustworthy computing. In: Proceedings of the 2004 IEEE International Conference on Services Computing, SCC 2004, pp. 186–193. IEEE (2004)
Li, M., Zhao, J., Wang, L., Cai, S., Xie, B.: Cows: An internet-enriched and quality-aware web services search engine. In: IEEE International Conference on Web Services, ICWS 2011, pp. 419–427. IEEE (2011)
Al-Masri, E., Mahmoud, Q.: Understanding web service discovery goals. In: IEEE International Conference on Systems, Man and Cybernetics, SMC 2009, pp. 3714–3719. IEEE (2009)
Mui, L., Mohtashemi, M., Halberstadt, A.: A computational model of trust and reputation. In: Proceedings of the 35th Annual Hawaii International Conference on System Sciences, HICSS 2002, pp. 2431–2439. IEEE (2002)
Zhang, Y., Zheng, Z., Lyu, M.: Wsexpress: A qos-aware search engine for web services. In: IEEE International Conference on Web Services, ICWS 2010, pp. 91–98. IEEE (2010)
Godse, M., Bellur, U., Sonar, R.: Automating qos based service selection. In: IEEE International Conference on Web Services, ICWS 2010, pp. 534–541. IEEE (2010)
Solomon, A., Litoiu, M.: Business process performance prediction on a tracked simulation model. In: Proceeding of the 3rd International Workshop on Principles of Engineering Service-Oriented Systems, pp. 50–56. ACM (2011)
Chen, L., Feng, Y., Wu, J., Zheng, Z.: An enhanced qos prediction approach for service selection. In: IEEE International Conference on Services Computing, SCC 2011, pp. 727–728. IEEE (2011)
Shao, L., Zhang, J., Wei, Y., Zhao, J., Xie, B., Mei, H.: Personalized qos prediction forweb services via collaborative filtering. In: IEEE International Conference on Web Services, ICWS 2007, pp. 439–446. IEEE (2007)
Maximilien, E., Singh, M.: Toward autonomic web services trust and selection. In: Proceedings of the 2nd International Conference on Service Oriented Computing, pp. 212–221. ACM (2004)
Malik, Z., Bouguettaya, A.: Rateweb: Reputation assessment for trust establishment among web services. The VLDB Journal 18(4), 885–911 (2009)
Shumway, R., Stoffer, D.: Time series analysis and its applications. Springer (2000)
Wang, L., Liu, F., Zhang, L., Li, G., Xie, B.: Enriching descriptions for public web services using information captured from related web pages on the internet. In: Fifth IEEE International Symposium on Service Oriented System Engineering, SOSE 2010, pp. 141–150. IEEE (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, M., Hua, Z., Zhao, J., Zou, Y., Xie, B. (2012). ARIMA Model-Based Web Services Trustworthiness Evaluation and Prediction. In: Liu, C., Ludwig, H., Toumani, F., Yu, Q. (eds) Service-Oriented Computing. ICSOC 2012. Lecture Notes in Computer Science, vol 7636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34321-6_51
Download citation
DOI: https://doi.org/10.1007/978-3-642-34321-6_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34320-9
Online ISBN: 978-3-642-34321-6
eBook Packages: Computer ScienceComputer Science (R0)