DocumentCode :
185685
Title :
Data mining meets network analysis: Traffic prediction models
Author :
Eterovic, Teo ; Mrdovic, Sasa ; Donko, Dzenana ; Juric, Zeljko
fYear :
2014
fDate :
26-30 May 2014
Firstpage :
1479
Lastpage :
1484
Abstract :
Most research on network traffic prediction has been done on small datasets based on statistical methodologies. This research analyzes an internet traffic dataset spanning multiple months using the data mining process. Each data mining phase was carefully fitted to the network analysis domain and systematized in context of data mining. The second part of the paper evaluates various seasonal time series prediction models (univariate), including ANN, ARIMA, Holt Winters etc., as a data mining phase on the given dataset. The experiments have shown that in most cases ANNs are superior to other algorithms for this purpose.
Keywords :
data mining; prediction theory; telecommunication computing; telecommunication traffic; ANN; ARIMA; Holt Winters; Internet traffic dataset; data mining; network analysis domain; network traffic prediction models; statistical methodologies; time series prediction models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 37th International Convention on
Conference_Location :
Opatija
Print_ISBN :
978-953-233-081-6
Type :
conf
DOI :
10.1109/MIPRO.2014.6859800
Filename :
6859800
Link To Document :
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