Particle Filtering Based Availability Prediction for Web Services
Guaranteeing the availability of Web services is a significant challenge due to unpredictable number of invocation requests the Web services have to handle at a time, as well as the dynamic nature of the Web. The issue becomes even more challenging for composite Web services in the sense that their availability is inevitably affected by corresponding component Web services. Current Quality of Service (QoS)-based selection solutions assume that the QoS of Web services (such as availability) is readily accessible and services with better availability are selected in the composition. Unfortunately, how to real-time maintain the availability information of Web services is largely overlooked. In addition, the performance of these approaches will become questionable when the pool of Web services is large. In this paper, we tackle these problems by exploiting particle filtering-based techniques. In particular, we have developed algorithms to precisely predict the availability of Web services and dynamically maintain a subset of Web services with higher availability. Web services can be always selected from this smaller space, thereby ensuring good performance in service compositions. Our implementation and experimental study demonstrate the feasibility and benefits of the proposed approach.
KeywordsService Composition Service Selection Composite Service Service Availability Unpredictable Number
Unable to display preview. Download preview PDF.
- 1.Benatallah, B., Sheng, Q.Z., Dumas, M.: The Self-Serv Environment for Web Services Composition. IEEE Internet Computing 7(1) (January/February 2003)Google Scholar
- 2.Domingue, J., Fensel, D.: Toward A Service Web: Integrating the Semantic Web and Service Orientation. Service Web 3.0 Project, http://www.serviceweb30.eu
- 3.Elsayed, A.: Reliability Engineering. Addison-Wesley (1996)Google Scholar
- 5.Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann (2006)Google Scholar
- 6.Kim, S., Rosu, M.: A Survey of Public Web Services. In: Proceedings of the 13th International World Wide Web Conference (WWW 2004), New York, NY, USA (May 2004)Google Scholar
- 8.Liu, Y., Ngu, A., Zeng, L.: QoS Computation and Policing in Dynamic Web Service Selection. In: Proceedings of the 13th International World Wide Web Conference (WWW 2004), New York, NY, USA (May 2004)Google Scholar
- 9.Maamar, Z., Sheng, Q.Z., Benslimane, D.: Sustaining Web Services High Availability Using Communities. In: Proceedings of the 3rd International Conference on Availability, Reliability, and Security (ARES 2008), Barcelona, Spain (March 2008)Google Scholar
- 11.Salas, J., Pérez-Sorrosal, F., Patiño-Martínez, M., Jiménez-Peris, R.: WS-Replication: A Framework for Highly Available Web Services. In: Proceedings of the 15th International Conference on World Wide Web (WWW 2006), Edinburgh, Scotland (May 2006)Google Scholar
- 12.Serrano, D., Patiño-Martìnez, M., Jimenez-Peris, R., Kemme, B.: An Autonomic Approach for Replication of Internet-based Services. In: Proceedings of the 27th IEEE International Symposium on Reliable Distributed Systems (SRDS 2008), Napoli, Italy (October 2008)Google Scholar
- 14.Sheng, Q.Z., Maamar, Z., Yu, J., Ngu, A.H.: Robust Web Services Provisioning Through On-Demand Replication. In: Proceedings of the 8th International Conference on Information Systems Technology and Its Applications (ISTA 2009), Sydney, Australia (April 2009)Google Scholar
- 18.Zeng, L., Benatallah, B., Dumas, M., Kalagnanam, J., Sheng, Q.Z.: Quality Driven Web Services Composition. In: Proceedings of The 12th International World Wide Web Conference (WWW 2003), Budapest, Hungary (2003)Google Scholar