A Decision Tree Based Predictive Self-Healing for Composite Web Services

Abstract

Web Service composition is an important feature of Web Services technology, which solves complex business problems by combining available services and ordering them to best suit the problem requirements. However, as services are deployed on the unreliable Internet, and as they are often long running, loosely coupled, and cross administrative boundaries, failures are expected to happen frequently during the execution of composite services. Thus, when one component service fails, composite Web Service does not operate appropriately and it effects on the execution of whole process. The easy solution to this problem is to reselect the service every time service fails. However, it is not feasible due to the high complexity of the reselection, which will interrupt the execution of composite service, lead to an extra delay and influence the performance of the composite service. In this paper,we propose a decision tree based approach on predictive self-healing for composite Web Service. In our approach,we first propose a self-healing cycle which has three phases such as monitoring, diagnostics and repair. Next, in order to minimize a number of reselections, we propose decision tree based performance prediction approach. With our approach, the component services which have previously violated QoS parameter values can be predicted. We will demonstrate that proposed solution has better performance in supporting the self-healing Web Service composition comparing to traditional way.