Decision Support for Dynamic Adaptation of Business Systems Based on Feature Binding Analysis

Dynamic evolution has been an essential requirement for more and more business systems which attempt to provide 7(days) x 24(hours) availability and flexible adaptability on the changing business environment. Therefore, these systems are expected to be self-adaptable at run-time with little user intervention. CBSD provides an architectural way for self-adaptation, in which adaptation can be performed on the macro level of architecture and easier to control. However, the big gap between the problem space (business goal and environment) and the solution space (software architecture and components), and the runtime decision-making for adaptation are two difficulties for the implementation of business-oriented self-adaptation. In this paper, we propose an approach of decision support for dynamic adaptation of business systems based on feature binding analysis. In the method, feature model is introduced to represent the business policy and bridge the gap. So, dynamic adaptation can first be performed on feature binding analysis. The other characteristic of the method is CBR (case based reasoning) based adaptation decision on environment factors captured by all kinds of sensors.