An autonomic computing system is a hardware/software environment in which an intelligent program, called a correlation engine, monitors events that are occurring, within the system, to determine if corrective action needs to be taken, and then orders directives for action if they are needed. The goal of an autonomic computing system is to keep the hardware and software environment as healthy as possible, with as little human intervention as possible. The correlation engine is responsible for analyzing real-time event data, determining if there is a problem, and then issuing the directive needed to solve the problem.

This paper discusses the role of ontologies in autonomic computing systems. An ontology is a formalized representation of the components of an application domain that represents a shared understanding of that domain, and allows for information exchange across domains. One can think of an ontology as a generalization of the concept of an information model. Ontologies are needed in autonomic computing systems, the authors argue, to provide a representation scheme so that a correlation engine can make sense out of a wide variety of disparate events that are occurring, and so that correlation engines from different domains can work together and share information.

The authors discuss correlation engines in general, and then provide an ontology for a specific correlation engine: eAutomation. The paper is well written and informative, both conceptually and through a specific example. It would be of interest to researchers who are interested in ontologies in general, since it provides a good example of using ontologies. It would also be of interest to researchers concerned with correlation engines, since it provides an advance in this technology.