Towards a Self-Healing Network in Controlling Access to Network Applications

A self-healing network is a ‘dream’ for every network designer today. Abstractly it is a network that capable of maintaining the availability of network services. This would not be impossible to be turned into a reality if the networks are embedded with intelligence. By having the intelligent capability the network can be self-managed in response to events that taken place within the network itself through the learning mechanisms. This paper presents the User Manager Agent System (UMAS) learning performance in controlling a request for network application session. ANFIS of Matlab v5.3 has been used to simulate the learning process in which it bases on the training data of network state. The work also had revealed some weaknesses of ANFIS in processing a large volume of training data sets and substantial amount of time taken for processing.