An Application of Neural Network and Rule-Based System for Network Management: Application Level Problems
Proceedings of the Thirtieth Hawaii International Conference on System Sciences (1997)
Jan. 3, 1997 to Jan. 6, 1997
Nittida Nuansri , Department of Computer Science and Computer Engineering
Tharam S. Dillon , Department of Computer Science and Computer Engineering
Samar Singh , Department of Computer Science and Computer Engineering
The more complex a network becomes, the more reliable and intelligent a network management system must be to consistently monitor the network and detect abnormal situations in a timely manner as they occur. Expert system techniques have been widely accepted to create network management systems. Despite the fact that there are a number of network management systems, most of them deal only with problems at the lower layers of the network hierarchy (the data link, or the network layer). The nature of problems at the application level signifi- cantly differs from of those that occur at the lower levels. Lower layer problems are well-understood while problems at the application level are complex, application dependent, and distinct from one another. Consequently, a network management system, in particular a fault management system, used at this level should be able to cope with these difficulties and dependencies. We propose a hybrid system which consists of neural network module and a rule-based system for monitoring and diagnosing problems occur at the application level. The domain name system (DNS) was selected as a testbed application for the prototype system.
N. Nuansri, T. S. Dillon and S. Singh, "An Application of Neural Network and Rule-Based System for Network Management: Application Level Problems," 30th Hawaii International Conference on System Sciences (HICSS), Maui, Hawaii, 1997, pp. 474.