Fuzzy logic based modelling and analysis of network traffic

Rahman, A; Kennedy, P; Simmonds, A; Edwards, J

Fuzzy logic based modelling and analysis of network traffic

Rahman, A Kennedy, P

Simmonds, A Edwards, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2008 IEEE 8th International Conference on Computer and Information Technology, CIT 2008, 2008, pp. 652 - 657
Issue Date:: 2008-09-22

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Field	Value	Language
dc.contributor.author	Rahman, A	en_US
dc.contributor.author	Kennedy, P https://orcid.org/0000-0001-7837-3171	en_US
dc.contributor.author	Simmonds, A	en_US
dc.contributor.author	Edwards, J https://orcid.org/0000-0002-7105-997X	en_US
dc.date.issued	2008-09-22	en_US
dc.identifier.citation	Proceedings - 2008 IEEE 8th International Conference on Computer and Information Technology, CIT 2008, 2008, pp. 652 - 657	en_US
dc.identifier.isbn	9781424423583	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10802
dc.description.abstract	Accurate computer network traffic models are required for many network tasks such as network traffic analysis and performance optimization. Existing statistical traffic modelling techniques rely on precise mathematical analysis of extensive measured data such as packet arrival time, packet size and server-side or client-side round trip time. With the advent of high speed broadband networks, gathering an acceptable quantity of data needed for the precise representation of traffic is a difficult, time consuming, expensive and in some cases almost an impossible task. In this work we developed a fuzzy logic based traffic models using imprecise data sets that can be obtained realistically. The model include a parameter, the R parameter, which is also useful for analysis of network traffic. © 2008 IEEE.	en_US
dc.relation.ispartof	Proceedings - 2008 IEEE 8th International Conference on Computer and Information Technology, CIT 2008	en_US
dc.relation.isbasedon	10.1109/CIT.2008.4594752	en_US
dc.title	Fuzzy logic based modelling and analysis of network traffic	en_US
dc.type	Conference Proceeding
utslib.for	080301 Bioinformatics Software	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Sydney, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Accurate computer network traffic models are required for many network tasks such as network traffic analysis and performance optimization. Existing statistical traffic modelling techniques rely on precise mathematical analysis of extensive measured data such as packet arrival time, packet size and server-side or client-side round trip time. With the advent of high speed broadband networks, gathering an acceptable quantity of data needed for the precise representation of traffic is a difficult, time consuming, expensive and in some cases almost an impossible task. In this work we developed a fuzzy logic based traffic models using imprecise data sets that can be obtained realistically. The model include a parameter, the R parameter, which is also useful for analysis of network traffic. © 2008 IEEE.

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http://hdl.handle.net/10453/10802