Traffic data collection system, traffic data collection method, and traffic data collection program

A method for collecting traffic data which is executed by a computer, the method comprising:

• receiving time-series data having a bandwidth value of a monitored network;
• extracting a feature amount of the time-series data from the time-series data having the bandwidth value by applying a seasonal adjustment method to the time-series data, wherein the extracting further comprises:
• decomposing, based on a parameter of scatterplot smoothing (Loess) (STL) decomposition adjusted to the time-series data, the time-series data into a trend term, a seasonality term, and a residual error term, by applying seasonal and trend decomposition using locally estimated STL decomposition to the time-series data having the bandwidth value, and
• extracting the feature amount of the time-series data from the trend term, the seasonality term, and the residual error term;
• adjusting a parameter of the STL decomposition based on a change in size of the time-series data when the parameter is changed by determining whether a change in size of the time-series data exceeds a threshold, adjusts the parameter that is strength of seasonality in a case where the change in size of the time-series data does not exceed the threshold, and adjusts the parameter that is the number of trend change points in a case where the change in size of the time-series data exceeds the threshold;
• transmitting the feature amount of the time-series data via a network for collecting traffic data of the monitored network;
• receiving the feature amount of the time-series data via the network for collecting traffic data of the monitored network;
• and
• recovering the time-series data having the bandwidth value from the feature amount of the time-series data.

A computer-readable non-transitory recording medium storing computer-executable program instructions that when executed by a processor cause a computer to execute operations comprising:

• receiving time-series data having a bandwidth value of a monitored network;
• extracting a feature amount of the time-series data from the time-series data having the bandwidth value by applying a seasonal adjustment method to the time-series data, wherein the extracting further comprises:
• decomposing, based on a parameter of scatterplot smoothing (Loess) (STL) decomposition adjusted to the time-series data, the time-series data into a trend term, a seasonality term, and a residual error term, by applying seasonal and trend decomposition using locally estimated STL decomposition to the time-series data having the bandwidth value, and
• extracting the feature amount of the time-series data from the trend term, the seasonality term, and the residual error term;
• adjusting a parameter of the STL decomposition based on a change in size of the time-series data when the parameter is changed by determining whether a change in size of the time-series data exceeds a threshold, adjusts the parameter that is strength of seasonality in a case where the change in size of the time-series data does not exceed the threshold, and adjusts the parameter that is the number of trend change points in a case where the change in size of the time-series data exceeds the threshold;
• transmitting the feature amount of the time-series data via a network for collecting traffic data of the monitored network;
• receiving the feature amount of the time-series data via the network for collecting traffic data of the monitored network;
• and
• recovering the time-series data having the bandwidth value from the feature amount of the time-series data.