Automated Fault Detection for Web Services using Naïve Bayes Approach

Abstract

With the development of the web service technology, the service application becomes an important and popular solution for the distributed computing model. As more and more web services are deployed on the network, the web services can fail for many reasons. One of challenges in this evolution is how to provide a necessary fault detection method for minimizing the service failure impact and enhance the reliability of the services. For this purpose, we present an automatic fault detection framework and a fault detection model based on the Naïve Bayes approach. By analyzing the available service execution logs, our method can achieve the training data and convert them into the detection model. Using the Naïve Bayes approach and the given threshold value, our model computes the service posterior probability to each fault type and identifies the service faults. Experimental results show that our method is effective in detecting the service faults.