| 摘要 |
<p><P>PROBLEM TO BE SOLVED: To automatically discriminate presence or absence of periodicity in traffic volume variation in a network. <P>SOLUTION: Collected traffic data are time-sequentially stored in a storage device by an input-standby device 51, the time-sequential traffic data stored in the storage device are read and subjected to fast Fourier transform by an input time-sequential/spectrum decomposing device 52, and only predetermined frequency components (for one day, one week, one month, or one year) are extracted from fast Fourier transform result data by a specific spectrum extracting device 53. A spectrum/extraction time-sequence-converting device 54 performs inverse Fourier transform on the extracted frequency components, a correlation value between an inverse Fourier transform result and the fast Fourier transform result is calculated by an input time-sequence/extraction time-sequence comparing device 55, and the calculated correlation value is compared with a predetermined threshold by an input time-sequence classifying device 56 to discriminate the presence or absence of periodicity of the collected traffic data. <P>COPYRIGHT: (C)2011,JPO&INPIT</p> |
