Predicting the quality of web services based on two layer model

Abstract

Recently, Web service has become an important issue in the research community. Especially, predicting the Quality of Service (QoS) for users has been a hot topic which needs researching and applicating. In the other hand, with the rapid growth of the number of service providers and users, it results a large number of datasets. It significantly effects on the QoS as management and supervision to describe the functional and non-functional characteristics of Web service. In this context, predicting QoS on big data dataset is an urgent issue that needs to be solved. In this paper, we present a new model to handle this issue based on a Restricted Boltzmann Machines (RBM), it is called Two Layer Model (TLM). We have used this model to deal with the big data datasets and the model used in efficient learning and inference procedures to predict the missing QoS value of web service. Our experiments have been performed based on two data sets in the WS-DREAM dataset and the experimental results have proved that the proposed model was effective.