One of the problems that hinders large scale network management tasks is the number of possible heterogeneous data sources that provide network information and how to
focus on a desired network segment without requiring a deep knowledge of the network structure. This work investigates how
to intelligently and efficiently refine and manage a vast amount of network monitoring data sources, by using artificial intelligent
reasoning through an intuitive user interface. We aim to minimise the user interaction and required user knowledge when searching for the desired network monitoring information by refining the presented information based on user choices. The concept of Ontology is utilised to create a knowledge base of multiple different aspects of our testbed: Internal Management structure, Physical Location of data sources, and network switch meta-data.
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
2nd International Conference on Computing Technology and Information Management
Citation
KYRIAKOPOULOS, K.G., PARISH, D.J. and WHITLEY, J.N., 2015. Flowstats: an ontology based network management tool. Second International Conference on Computing Technology and Information Management (ICCTIM), Universiti Tun Hussein Onn, Malaysia, 21-23Apr, pp. 13-18.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/