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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/18772

Title: Flowstats: an ontology based network management tool
Authors: Kyriakopoulos, Konstantinos G.
Parish, David J.
Whitley, John N.
Keywords: Network management
Netflow
Ontology
RDF
Databases
Issue Date: 2015
Publisher: © IEEE
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.
Abstract: 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.
Description: 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
Version: Submitted for publication
DOI: 10.1109/ICCTIM.2015.7224586
URI: https://dspace.lboro.ac.uk/2134/18772
Publisher Link: http://dx.doi.org/10.1109/ICCTIM.2015.7224586
ISBN: 9781479962105
Appears in Collections:Pre-Prints (Mechanical, Electrical and Manufacturing Engineering)

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