The work considers a one-dimensional time series protocol packet intensity, measured on the city backbone network. The intensity of the series is uneven. Scattering diagrams are constructed. The Dickie Fuller test and Kwiatkowski-Phillips Perron-Shin-Schmitt test were applied to determine the initial series to the class of stationary or non-stationary series. Both tests confirmed the involvement of the original series in the class of differential stationary. Based on the Dickie Fuller test and Private autocorrelation function graphs, the Integrated Moving Average Autoregression Model model is created. The results of forecasting network traffic showed the adequacy of the selected model
Abstract: In order to maintain consistent quality of service, computer network engineers face the ta...
The dynamics of data traffic intensity is examined using traffic measurements at the interface switc...
Abstract — Short period prediction is a relevant task for many network applications. Tuning the para...
The work considers a one-dimensional time series protocol packet intensity, measured on the city ba...
The paper presents the results of building neural network predictive models of the occupancy of the ...
This paper presents an approach for a network traffic characterization by using statistical techniqu...
We investigate the stationarity property of the accumulated Ethernet traffic series. We applied seve...
A time-series data analysis and prediction tool for learning the network traffic usage data is very ...
In this paper non-linear threshold autoregressive models are examined for use in modeling the tempor...
Theses deals with network traffic modeling focused on elaboration by time series analysis. The natur...
Traffic behavior in a large-scale network can be viewed as a complicated non-linear system, so it is...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
Data traffic sequences from two campus FDDI rings, an Ethernet, two entry/exit points of the NSFNET...
Fast and accurate methods for predicting traffic properties and trend are essential for dynamic netw...
Abstract: In order to maintain consistent quality of service, computer network engineers face the ta...
The dynamics of data traffic intensity is examined using traffic measurements at the interface switc...
Abstract — Short period prediction is a relevant task for many network applications. Tuning the para...
The work considers a one-dimensional time series protocol packet intensity, measured on the city ba...
The paper presents the results of building neural network predictive models of the occupancy of the ...
This paper presents an approach for a network traffic characterization by using statistical techniqu...
We investigate the stationarity property of the accumulated Ethernet traffic series. We applied seve...
A time-series data analysis and prediction tool for learning the network traffic usage data is very ...
In this paper non-linear threshold autoregressive models are examined for use in modeling the tempor...
Theses deals with network traffic modeling focused on elaboration by time series analysis. The natur...
Traffic behavior in a large-scale network can be viewed as a complicated non-linear system, so it is...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
Data traffic sequences from two campus FDDI rings, an Ethernet, two entry/exit points of the NSFNET...
Fast and accurate methods for predicting traffic properties and trend are essential for dynamic netw...
Abstract: In order to maintain consistent quality of service, computer network engineers face the ta...
The dynamics of data traffic intensity is examined using traffic measurements at the interface switc...
Abstract — Short period prediction is a relevant task for many network applications. Tuning the para...