Implementing context-aware performance management in intelligent SOA middleware

Service-Oriented Architecture (SOA) is a software paradigm with a uniform means to offer, discover, compose services' capabilities to meet desired effects with measurable performance expectations. While most of today's SOA tools support service process compositions by considering only functional attributes, additional support for composing service processes by non-functional attribute is needed. In this paper, we present an approach to improve the performance of a business process by introducing context as a non-functional attribute. During normal service executions, each service's actual performance is collected and used to build service performance profile under a context tree. We then use the K-means clustering algorithm to classify and record context dependency on the observed service performance. We also study algorithms to decide the clustering unit of context attribute values and to distinguish those context attributes that may or may not significantly affect service performance. Simulation result shows that our methodologies are effective for context aware management.