Abstract: Self-monitoring of autonomic distributed systems requires knowledge of the
states and events of many different parts of a system. One of the main
challenges is to determine which information is most crucial for analysis of
a system's behaviour, and when. This paper proposes a model-based approach
to self-monitoring for which structural and behavioural models of a system
are described at different levels: application, subsystem, component and
class level. In this approach, a system's behaviour is monitored in the
context of a hierarchy of use-cases related to these levels. The structural
and behavioural models are used to automatically instrument an existing
distributed system. The proposed architecture of a self-monitoring engine is
described as is the implementation. The models have been specified in the
Ontology Web Language (OWL) and the self-monitoring (as a part of our
self-management framework) has been implemented in Java. The scenario used
to illustrate the approach is that of authentication for a simplified
version of a distributed portal application.
Abstract: Automated support for management of complex distributed object-oriented systems is a challenge: self-management the goal. A self-management system needs to reason about the behaviour of the distributed entities in a system, and act when necessary. The knowledge needed is multi-leveled: different levels of concepts and rules need to be represented. This paper explores the requirements that hold for representing this knowledge in self-managed distributed object-oriented systems, and explores the potential of Semantic Web technology in this context. A model for self-management knowledge and a simplified version of a real-life use case are used to illustrate the potential.