Generative policy model for autonomic management

Abstract

Policy-based mechanisms have been effectively used to realize autonomic behavior in the constituent elements of distributed systems. However, current prevalent policy models based on event-condition-Action rules are not sufficient to deal with highly dynamic environments. They tend to rely on fixed policy structures for the automated enforcement of predefined directives. A higher level of autonomic behavior can be enabled if the managed system could be given greater flexibility in its operations, while maintaining the consistency and compliance with requirements that have led to the successes of the policy based management paradigm. In this paper, we present a new approach that employs policy structures that are more dynamic and contextual while still preserving the desired levels of control, thus allowing managed systems to take more autonomic decisions regarding their operations.