Rule Based Reasoning for Network Management

This paper focuses on improving network management by the adoption of artificial intelligence techniques. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as a managing entity capable of directing, coordinating, and triggering monitoring and management actions in the proposed architecture. The logical inference system has been devised to enable automated isolation, diagnosis, and to repair network anomalies, thus enhancing the reliability, performance, and security of the network. The measurements of network events are captured by programmable sensors deployed on the network devices and are collected by the network management entity where they are merged with general domain knowledge, with a view to identifying the root causes of anomalies, and to decide on reparative actions. The relevant results inferred by the logical reasoner and the significant events occurred on the network are stored both in a global DB and in local distributed DBs, in order to enable successive analyses of network events. In order to illustrate the advantages and potential benefits deriving from the reasoning capabilities of our management system, the results of preliminaries experiments are analyzed.