Autonomic Configuration Adaptation Based on Simulation-Generated State-Transition Models
Configuration management is a complex task, even for experienced system administrators, which makes self-managing systems a particularly desirable solution. This paper describes a novel contribution to self-managing systems, including an autonomic configuration self-optimization methodology. The authors' solution involves a systematic simulation method that develops a state-transition model of the behavior of a service-oriented system in terms of its configuration and performance. At run time, the system's behavior is monitored and classified in one of the model states. If this state may lead to futures that violate service level agreements, the system configuration is changed toward a safer future state. Similarly, a satisfactory state that is over-provisioned may be transitioned to a more economical satisfactory state.