Q-Mon: An adaptive SOA system with data mining
Xinhuai Tang, Jiang Ge · 2016
Traditional SOA system frequently fails to execute services after the service composition. We address these shortcomings with Q-Mon, and efficient, reliable SOA system to find the rules between the environment and the executed service. Q-Mon provides real time replacement by choosing another service to execute, which is predicted to have a good performance in the current context. Q-Mon monitors the behavior of the executing service and the environment, and the collected data is used for relationship mining. Our experimental results show that Q-MON reduces the response time drastically and also predicts suitable service to replace the failed one for executing.