Dynamic web service discovery

Existing methods used for service discovery assume that the world is static, considering a predetermined set of attributes. As a result, current discovery techniques return many results that are irrelevant. Our approach to high quality service discovery improves the results’ relevancy by considering dynamic attributes with values changing over time. Using this approach, we reveal structure from the data to satisfy the consumers’ experiences. Web service quality is a set of dynamic attributes used to rank services with similar functionalities. When picking a service to execute financial transactions efficiently, we might consider availability, reliability, response time, and transaction cost as quality indicators. Supporting dynamic attributes is a feature critical to providing exceptional quality service discovery. In addition, effective service discovery requires detailed context models that describe both static and dynamic features. The context takes into consideration the situation of the service, the operating environment, the users’ circumstances, and their preferences. For instance, latency is an important issue in stock trading services with direct impact on revenue. One of the main challenges in enabling dynamic service discovery is developing techniques and models to handle the novel aspects of the web service paradigm. This