PREVENTION OF FAULT PROPAGATION IN WEB SERVICE: A COMPLEX NETWORK APPROACH
Keywords:Web Service Complex Network, invocable relation between services, fault propagation, loads allocation strategy
How to prevent the fault propagation problems in Web Service has become an important issue. The recent research works mostly take some fault tolerance method in service based system. These methods detect or diagnose faults in the composition process, find the failure service, take tolerance action and recover the system. However, in the service oriented architecture, one service is shared by different service based systems. The fault tolerance method only considers from the view of one service user, and tolerance action not considering the whole network would change its load and even the global redistribution of loads over all of the services, trigger a cascade of overload, and result in service network paralysis. The research of cascading failure in Complex Network provides a set of models to help study the above problems. Consequently, this paper proposes a new approach to deal with the fault propagation for Web Service from the view point of the whole service network, which could analyze its resistance influenced by the size of network, different types of attacks and load allocation strategies and prevent the disasters from happening. Firstly, it constructs a Web Service Complex Network (WSCN) composed of single service and their functional similarity. Then it models fault propagation based on WSCN, and simulates the propagation process by analyzing WSCN performance under small attack, large attack, random attack and calculated attack. When fault happens in WSCN, our method uses weight-based and spare-load-based load allocation methods of failed service to compare their influences on the whole network. The experimental results show that when fault happens in WSCN, the network has better resistance for small scale failure than big scale one, and resists stronger for random attack than deliberate one; when the service failure happens, the remaining space based load allocation strategy on it has higher robustness than weight based one. The simulation of fault propagation for Web Service could set example for preventing and reducing probabilities of collapse in the service network.
Papazoglou, M. P. (2003, December). Service-oriented computing: Concepts, characteristics and
directions. In Web Information Systems Engineering, 2003. WISE 2003. Proceedings of the
Fourth International Conference on (pp. 3-12). IEEE.
Erl, T. (2004). Service-oriented architecture: a field guide to integrating XML and web services.
Prentice Hall PTR.
Hwang, S. Y., Lim, E. P., Lee, C. H., & Chen, C. H. (2008). Dynamic web service selection for
reliable web service composition. Services Computing, IEEE Transactions on, 1(2), 104-116.
Chan, K. M., Bishop, J., Steyn, J., Baresi, L., & Guinea, S. (2009, January). A fault taxonomy for
web service composition. In Service-oriented computing-ICSOC 2007 Workshops (pp. 363-375).
Springer Berlin Heidelberg.
Y. Yan, P. Dague, Y. Pencole, and M.O. Cordier. A model-based approach for diagnosing fault in
web service processes. International Journal of Web Services Research (IJWSR), 6(1):87-110,
A. Erradi, P. Maheshwari, and V. Tosic. Recovery policies for enhancing web services reliability.
In Web Services, 2006. ICWS'06. International Conference on, pages 189-196. IEEE, 2006.
W. He. Recovery in web service applications. In e-Technology, e-Commerce and e-Service, 2004.
EEE'04. 2004 IEEE International Conference on, pages 25-28. IEEE, 2004.
Z. Zhu, J. Li, Y. Zhao, and Z. Li. Scenetester: A testing framework to support fault diagnosis for
web service composition. In Computer and Information Technology (CIT), 2011 IEEE 11th
International Conference on, pages 109-114. IEEE, 2011.
G. Friedrich, M. Fugini, E. Mussi, B. Pernici, and G. Tagni. Exception handling for repair in
service-based processes. Software Engineering, IEEE Transactions on, 36(2):198-215, 2010.
Motter, A. E., & Lai, Y. C. (2002). Cascade-based attacks on complex networks. Physical Review
E, 66(6), 065102.
Crucitti, P., Latora, V., Marchiori, M., & Rapisarda, A. (2004). Error and attack tolerance of
complex networks. Physica A: Statistical Mechanics and its Applications, 340(1), 388-394.
Yau, S. S., Ye, N., Sarjoughian, H. S., Huang, D., Roontiva, A., Baydogan, M., & Muqsith, M. A.
(2009). Toward development of adaptive service-based software systems. Services Computing,
IEEE Transactions on, 2(3), 247-260.
J. Zhou, K. Cooper, I. Yen and R. Paul, Rule-Base Technique for Component Adaptation to
Support QoS-Based Reconfiguration, Proc. Ninth IEEE Int',l Symp. Object-Oriented Real-Time
Distributed Computing, pp. 426-433, May 2005.
Bak, P., Tang, C., & Wiesenfeld, K. (1987). Self-organized criticality: An explanation of 1/f noise.
Physical Review Letters, 59(4), 381-384.
Motter, A. E. (2004). Cascade control and defense in complex networks. Physical Review Letters,
Moreno, Y., Gómez, J. B., & Pacheco, A. F. (2002). Instability of scale-free networks under nodebreaking
avalanches. EPL (Europhysics Letters), 58(4), 630.
Kinney, R., Crucitti, P., Albert, R., & Latora, V. (2005). Modeling cascading failures in the North
American power grid. The European Physical Journal B-Condensed Matter and Complex Systems,
Bao, Z. J., Cao, Y. J., Ding, L. J., Han, Z. X., & Wang, G. Z. (2008). Dynamics of load entropy
during cascading failure propagation in scale-free networks. Physics Letters A, 372(36), 5778-
Crucitti, P., Latora, V., & Marchiori, M. (2004). A topological analysis of the Italian electric
power grid. Physica A: Statistical Mechanics and its Applications, 338(1), 92-97.
Liu, A., Li, Q., Huang, L., & Xiao, M. (2010). Facts: A framework for fault-tolerant composition
of transactional web services.Services Computing, IEEE Transactions on,3(1), 46-59.
S. Kona, A. Bansal, M. B. Blake, S. Bleul, T. Weise, WSC-2009: A Quality of Service-Oriented
Web Services Challenge, IEEE Computer Society, pp.487-490, Vienna, Austria, 2009.