Automatic Diagnosis for Composite Web Service in Cloud Computing

Abstract:

Cloud computing is becoming a popular and important platform for web service applications. With the advent of more and more service resources in cloud, it is a crucial challenge to build an effective diagnostic mechanism. To improve the diagnosis capability for composite web service, we propose an automatic diagnostic framework and a hybrid diagnosis method for diagnosing the faulty activities. Our diagnostic framework can improve the scalability of diagnostic system and add the diagnostic capability of diagnosis service by decoupling the diagnostic service components. Our diagnosis method identifies the differences between successful and failed executions for finding the incorrect activities of the composite service and provides faulty causes by considering the structured activities in the process of diagnosis. Experimental results show that our method is effective to the composite web service in the fault diagnosis.

• Periodical: Applied Mechanics and Materials (Volumes 347-350)
• Pages: 2311-2316
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.347-350.2311
• Online since: August 2013
• Authors: Zhi Chun Jia, Rong Chen, Jun Jie Xu
• Keywords: Activity Dependence Graph, Cloud Computing, Composite Web Service, Fault Diagnosis

References

[1] Y. Yan, P. Dague, Y. Pencole , and M. -O. Cordier, A Model-based Approach for Diagnosing Faults in Web Service Processes, The International Journal of Web Services Research (JWSR), vol. 6, pp.87-110, (2009).

DOI: 10.4018/jwsr.2009092205

[2] L. Ardissono, S. Bocconi, L. Console, R. Furnari, A. Goy, G. Petrone, et al., Enhancing Web Service Composition by Means of Diagnosis, Business Process Management Workshops, vol. 17, pp.468-479, (2008).

DOI: 10.1007/978-3-642-00328-8_47

[3] W. Mayer, G. Friedrich , and M. Stumptner, Diagnosis of Service Failures by Trace Analysis with Partial Knowledge, Service-Oriented Computing, vol. 6470, pp.334-349, (2010).

DOI: 10.1007/978-3-642-17358-5_23

[4] Y. Li, L. Ye, P. Dague , and T. Melliti, A Decentralized Model-Based Diagnosis for BPEL Services, " Proceedings of the 2009 21st IEEE International Conference on Tools with Artificial Intelligence (ICTAI , 09 ), pp.609-616, (2009).

DOI: 10.1109/ictai.2009.77

[5] M. Alodib and B. Bordbar, A model-based approach to Fault diagnosis in Service oriented Architectures, " ECOWS, 09 - 7th IEEE European Conference on Web Services, pp.129-138, (2009).

DOI: 10.1109/ecows.2009.13

[6] L. Ardissono, L. Console, A. Goy, G. Petrone, C. Picardi, M. Segnan, et al., Cooperative Model-Based Diagnosis of Web Services, Proceedings of 16th International Workshop on Principles of Diagnosis (2005).

DOI: 10.1109/ecows.2005.12

[7] X. Han, Z. Shi, W. Niu, K. Chen , and X. Yang, Similarity-Based Bayesian Learning from Semi-structured Log Files for Fault Diagnosis of Web Services, presented at the Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on, (2010).

DOI: 10.1109/wi-iat.2010.51

[8] S. C. Hui, A. C. M. Fong , and G. Jha, A web-based intelligent fault diagnosis system for customer service support, Engineering Applications of Artificial Intelligence, vol. 14, pp.537-548, (2001).

DOI: 10.1016/s0952-1976(01)00018-5

[9] F. Moo-Mena, J. Garcilazo-Ortiz, L. Basto-Diaz, F. Curi-Quintal , and F. Alonzo-Canul, Defining a Self-Healing QoS-based Infrastructure for Web Services Applications. Los Alamitos: Ieee Computer Soc, (2008).

DOI: 10.1109/csew.2008.73

[10] L. Wang, X. Bai, L. Zhou , and Y. Chen, A Hierarchical Reliability Model of Service-Based Software System, " presented at the Computer Software and Applications Conference, 2009. COMPSAC , 09. 33rd Annual IEEE International, (2009).

DOI: 10.1109/compsac.2009.34

[11] H. N. Lakshmi and H. Mohanty, Automata for Web Services Fault Monitoring and Diagnosis, IJCCT, vol. 3, pp.13-18, (2011).

[12] Y. Dai, L. Yang, B. Zhang , and Z. Zhu, Exception diagnosis for composite service based on error propagation degree, 2011 IEEE International Conference on Services Computing, SCC 2011, pp.160-167, (2011).

DOI: 10.1109/scc.2011.109

[13] Z. Zhu and W. Dou, QoS-Based Probabilistic Fault-Diagnosis Method for Exception Handling, New Horizons in Web-Based Learning: Icwl 2010 Workshops, vol. 6537, pp.227-236, (2011).

DOI: 10.1007/978-3-642-20539-2_25

[14] K. Yu, M. Lin, Q. Gao, H. Zhang , and X. Zhang, Locating faults using multiple spectra-specific models, in Proceedings of the 2011 ACM Symposium on Applied Computing, TaiChung, Taiwan, 2011, pp.1404-1410.

DOI: 10.1145/1982185.1982490

[15] J. A. Jones and M. J. Harrold, Empirical evaluation of the tarantula automatic fault-localization technique, in Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering, Long Beach, CA, USA, 2005, pp.273-282.

DOI: 10.1145/1101908.1101949

[16] Y. Yu, J. A. Jones , and M. J. Harrold, An empirical study of the effects of test-suite reduction on fault localization, " presented at the Software Engineering, 2008. ICSE , 08. ACM/IEEE 30th International Conference on, (2008).

DOI: 10.1145/1368088.1368116

[17] R. Abreu, P. Zoeteweij, R. Golsteijn , and A. J. C. van Gemund, A practical evaluation of spectrum-based fault localization, Journal of Systems and Software, vol. 82, pp.1780-1792, (2009).

DOI: 10.1016/j.jss.2009.06.035

[18] E. Al-Masri and Q. H. Mahmoud, Investigating web services on the world wide web, in Proceedings of the 17th international conference on World Wide Web, Beijing, China, 2008, pp.795-804.

DOI: 10.1145/1367497.1367605