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Flowstats: an ontology based network management tool

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conference contribution
posted on 2015-09-15, 14:59 authored by Kostas KyriakopoulosKostas Kyriakopoulos, David Parish, John N. Whitley
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.

Publisher

© IEEE

Version

  • SMUR (Submitted Manuscript Under Review)

Publisher statement

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/

Publication date

2015

Notes

This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

ISBN

9781479962105

Language

  • en

Location

Universiti Tun Hussein Onn, Malaysia

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