A framework for learning and inference in network management

A network management framework which builds the management information infrastructure and equips the management applications with learning and reasoning abilities for automatic and adaptive management tasks is presented. Views consist of global virtual management information constructed by logical rules from the distributed physical management information. Through these views, management applications can access physical network entities. Management applications learn network patterns and reason on the discovered patterns and prespecified domain knowledge to predict network behavior, diagnose problems, and trigger control actions. The abstract view definitions, domain knowledge, and network patterns are a set of logical rules stored in the application-dependent MKB (management knowledge base), while the physical management information is stored in the standard MIB (management information base) at each node.<<ETX>>