An Adaptive Service Selection Approach to Service Composition

In service computing, the behavior of a service may evolve. When an organization develops a service-oriented application in which certain services are provided by external partners, the organization should address the problem of uninformed behavior evolution of external services. This paper proposes an adaptive framework that bars problematic external services to be used in the service-oriented application of an organization. We use dynamic WSDL information in public service registries to approximate a snapshot of a network of services, and apply link analysis on the snapshot to identify services that are popularly used by different service consumers at the moment. As such, service composition can be strategically formed using the highly referenced services. We evaluate our proposal through a simulation study. The results show that, in terms of the number of failures experienced by service consumers, our proposal significantly outperforms the random approach in selecting reliable services to form service compositions.

[1]  Allan Borodin,et al.  Link analysis ranking: algorithms, theory, and experiments , 2005, TOIT.

[2]  W. Chan,et al.  A Metamorphic Testing Approach for Online Testing of Service-Oriented Software Applications , 2007, Int. J. Web Serv. Res..

[3]  Danilo Ardagna,et al.  Adaptive Service Composition in Flexible Processes , 2007, IEEE Transactions on Software Engineering.

[4]  Richard S. Hall,et al.  Dynamic Contextual Service Ranking , 2007, SC@ETAPS.

[5]  Anne H. H. Ngu,et al.  QoS-aware middleware for Web services composition , 2004, IEEE Transactions on Software Engineering.

[6]  Carl K. Chang,et al.  WS-Net: a Petri-net based specification model for Web services , 2004 .

[7]  Shiyong Lu,et al.  Automatic workflow verification and generation , 2006, Theor. Comput. Sci..

[8]  Wonjun Lee,et al.  Context-Aware Service Composition for Mobile Network Environments , 2007, UIC.

[9]  Maria Fasli,et al.  Automatic Web Service Composition Based on Graph Network Analysis Metrics , 2005, OTM Conferences.

[10]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[11]  Manfred Broy,et al.  A formal model of services , 2007, TSEM.

[12]  Haifeng Chen,et al.  Failure Detection in Large-Scale Internet Services by Principal Subspace Mapping , 2007, IEEE Transactions on Knowledge and Data Engineering.

[13]  T. H. Tse,et al.  Data flow testing of service-oriented workflow applications , 2008, 2008 ACM/IEEE 30th International Conference on Software Engineering.

[14]  Hernán C. Melgratti,et al.  Testing Service Composition , 2007 .

[15]  Remco M. Dijkman,et al.  Service composition: concepts, techniques, tools and trends , 2005 .

[16]  Sebastián Uchitel,et al.  Model-based verification of Web service compositions , 2003, 18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings..

[17]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[18]  Valérie Issarny,et al.  Context-Aware Service Composition in Pervasive Computing Environments , 2005, RISE.

[19]  Hong Zhu,et al.  A Framework for Service-Oriented Testing of Web Services , 2006, 30th Annual International Computer Software and Applications Conference (COMPSAC'06).

[20]  Abdelkarim Erradi,et al.  AdaptiveBPEL: a Policy-Driven Middleware for Flexible Web Services Composition , 2005 .

[21]  Richard S. Hall,et al.  Autonomous adaptation to dynamic availability using a service-oriented component model , 2004, Proceedings. 26th International Conference on Software Engineering.

[22]  Raymond A. Paul,et al.  Testing Web Services Using Progressive Group Testing , 2004, AWCC.