An investigation of network management methods
Date of Award
Master of Computer Science
School of Computer and Information Science
Faculty of Computing, Health and Science
Associate Professor Dr. Paul Maj
Networks are populations of interconnected devices. Disruptions to connectivity even for a short time, can potentially affect a large number of users. Network Management (NM) is concerned with minimising problems and down time. There are a number of NM tools and models with the primary objective of managing networks. However, experts agree that many of these tools lack functionality. Furthermore, the models used are out of date. A new model that may assist in managing the network and may also used to train network administrators is the State Model Diagram (SMD). SMDs extract and diagrammatically integrate the output from different Command Line Interfaces (a complex and commonly used hierarchical text based tool for NM) and hence succinctly describe protocol operation. In addition, SMDs may be use to describe different network devices such as firewalls, wireless access points, routers, switches, etc. SMDs also provide top down decomposition thereby enabling a large complex network to be partition into independent units of an emendable size. This new model may provide functionality not currently offered by current NM tools. Furthermore, using SMDs it is possible to obtain increasing levels of detail whilst still maintaining links and interfaces between different levels, thereby supporting student learning both at introductory and advanced level. SMDs were evaluated as a NM tool and as a tool to teach NM. The positive responses from the four extensive experiments among 75 participants have clearly demonstrated that SMD's were found to be as useful as the CLI for all aspects of NM, and, significantly, students learning based on SMDs have gained a richer conceptual understanding strongly aligned with that of an expert. However, further work is required.
Tran, B. (2007). An investigation of network management methods. Retrieved from http://ro.ecu.edu.au/theses/263