Abstract: Service-oriented systems have become popular and presented many advantages in developing enterprise services. The service categorization is the inevitable process in web service composition for choosing most suitable services from the available services that suits to the users requirements. Many researchers propose several service categorization techniques like those that functional metric based service categorization and non-functional metric based service categorization. Nevertheless, those methods did not address the structural properties of the target services. We are proposing a structural metric based categorization technique for effective Web Services Composition (WSC). Coupling is the most important structural attribute of services when they integrated into a system. Structural metrics are useful to evaluate services quality according to its ability of coupling. We are aiming at using the coupling metrics to measure the maintainability, reliability, testability and reusability of services. We have identified two Service Colony Metrics (SCM) to formulate the Weighted Dependency Metric (WDM) which is used as the fitness function of Genetic Algorithm based Service Categorization (GASC) technique for optimizing the composite service categorization. This dependency metric based GASS technique have been tested in e-learning web services system and the experimental results shows improved performance when compared with non-functional metrics based categorization techniques.
M. Sathya, P. Dhavachelvan and G. Sureshkumar, 2010. Web Service Categorization Using Structural Metrics. International Journal of Soft Computing, 5: 164-170.