Supporting QoS based selection in service oriented architecture

The ability to gauge quality of service is critical if we are to realise the potential of the service-oriented computing paradigm. Many techniques have been proposed for calculating the quality of a service, and they do so typically by collecting quality ratings from the users of the service, then combining them in one way or another to derive the quality of the service. We argue that combining quality ratings in such a way may lead to inaccurate quality measures for services. This is because different users often have different expectations on the quality of a service and their ratings tend to be closely related to these expectations, i.e. how their expectations are met. In this paper, we propose a quality of service assessment model that is able to capture the reason behind the ratings. This allows us to perform quality of service assessment in context, by using only the ratings that have similar expectations. We also introduce a confidence score that adjusts a rating of harsh or lenient rater. This is established by analyzing a user's past rating behavior for services. Our experiments show that the method we propose here can result in more meaningful and reliable selection of services