A Runtime evaluation methodology and framework for autonomic systems

An autonomic system provides self-adaptive ability that enables system to dynamically adjust its behavior on environmental changes or system failure. Fundamental process of adaptive behavior in an autonomic system is consist of monitoring system or/and environment information, analyzing monitored information, planning adaptation policy and executing selected policy. Evaluating system utility is one of a significant part among them. We propose a novel approach on evaluating autonomic system at runtime. Our proposed method takes advantage of a goal model that has been widely used at requirement elicitation phase to capture system requirements. We suggest the state-based goal model that is dynamically activated as the system state changes. In addition, we defined type of constraints that can be used to evaluate goal satisfaction level. We implemented a prototype of autonomic computing software engine to verity our proposed method. We simulated the behavior of the autonomic computing engine with the home surveillance robot scenario and observed the validity of our proposed method.