Usage of RBF Networks in prediction of network traffic
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Annals of Computer Science and Information Systems Volume 2 Maria Ganzha, Leszek Maciaszek, Marcin Paprzycki (eds.) Position Papers of the 2013 Federated Conference on Computer Science and Information Systems September 8–11, 2013. Krak´ ow, Poland
Transcript of Usage of RBF Networks in prediction of network traffic
Annals of Computer Science and Information Systems
Volume 2
Maria Ganzha, Leszek Maciaszek, Marcin Paprzycki (eds.)
Position Papers of the 2013 FederatedConference on Computer Science and
Information Systems
September 8–11, 2013. Krakow, Poland
Annals of Computer Science and Information Systems
Series editors:Maria GanzhaSystems Research Institute Polish Academy of Sciences
and
University of Gdańsk, Gdańsk, Poland
Leszek MaciaszekWrocław Universty of Economy, Wrocław, Poland
and
Macquarie University, Sydney, Australia
Marcin PaprzyckiSystems Research Institute Polish Academy of Sciences
and
Warsaw Management Academy, Warsaw, Poland
TEXnical editor:Aleksander DenisiukUniversity of Warmia and Mazury, Olsztyn, Poland
Contact: [email protected]
WWW site: http://www.fedcsis.org/annals/
ISSN: 2300-5963
c� Polskie Towarzystwo InformatyczneAl. Solidarności 82A m. 5
01-003 Warsaw
Poland
Annals of Computer Science and Information Systems, Volume 2
Position Papers of the 2013Federated Conference on ComputerScience and Information Systems
Maria GanzhaLeszek Maciaszek
Marcin Paprzycki (eds.)
2013, Warszawa, Polskie Towarzystwo Informatyczne
Annals of Computer Science and Information Systems, Volume 2Position Papers of the 2013 Federated Conference on Computer Scienceand Information Systems (FedCSIS)
ISBN WEB: 978-83-60810-55-2ISBN USB: 978-83-60810-56-9
ISSN: 2300-5963
Also in this series:
Volume 1: Proceedings of the 2013 Federated Conference on Computer Science andInformation Systems (FedCSIS), ISBN WEB: 978-1-4673-4471-5, ISBN USB: 978-83-60810-53-8
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Usage of RBF Networks in prediction of network traffic 63
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vi
TABLE I.INVESTIGATED NETWORKS DESCRIPTION. SOURCE: OWN RESEARCH.
Symbol
escription
Amateur campus network consisting of circa 25 workstations. Snort has worked on the router which actsalso as the gateway to the Internet and as FTP, www, SAMBA and TeamSpeak servers Data werecollected from 13th September to 5th December 2006 with a ten minute interval (a total of 11 969measurements).
T2
Campus network provided by a mid-size Internet Access Provider – (about 400 clients). Data werecollected from 3rd January to 16th March 2007 with ten-minute intervals (a total of 10 001measurements) on the link between the network and the Internet in housing estates.
T3
A network in a block of flats; one of the subnetworks mentioned in the examples T2 containing about 20clients. The data were collected from 20th November 2006 to 16th March 2007 with ten-minute intervals(a total of 16402 measurements) on the same link as above (T2) but with address filtering.
MM
Home network connected to the campus amateur network (with maximum speed of inbound traffic seton the bandwidth manager to 4 Mbps. Home network consists of five computers protected by corporatefirewall and two intranet servers (ftp and PrintServer). The network has no servers providing outsideservices and there is no remote access to the home network from the outside. IDS was placed on the linkto the campus network before the firewall. The data were collected from 12 o 1 201120113 measurements
II
Local Area Network in small company (about 40 computers, two intranet servers). The data werecollected from 3 2011 4 2011 21747 measurements
Position papers of the 2013 Federated Conference onComputer Science and Information Systems pp. 63–66
c� 2013, PTI 63
64 POSITION PAPERS OF THE FEDCSIS. KRAKOW, 2013
TABLE II.RBF AND MLP ANNS STRUCTURES AND FIT. SOURCE: OWN RESEARCH.
MACIEJ SZMIT, ANNA SZMIT, MARCIN KUZIA: USAGE OF RBF NETWORKS 65
66 POSITION PAPERS OF THE FEDCSIS. KRAKOW, 2013
