Mapping Policies to a Causal Network for Diagnosis

Policy-based Autonomic Management monitors a system and its applications and tweaks performance parameters in real-time based on a set of governing policies. A policy specifies a set of conditions under which one or more of a set of actions are to be performed. It is common that multiple policies´ conditions are met simultaneously, each advocating actions. We propose a method of diagnosing the system to try to determine the best action or actions to perform in a given situation using Abductive Inference. We develop an original method of building a causality graph to facilitate diagnosis directly from a set of policies. Performance of the diagnosis method is measured by implementing diagnosis into an existing autonomic management application. The results are favourable when compared to previous methods of action selection.