  By studying the statistics of recurrence intervals, $\tau$, between
volatilities of Internet traffic rate changes exceeding a certain threshold
$q$, we find that the probability distribution functions, $P_{q}(\tau)$, for
both byte and packet flows, show scaling property as
$P_{q}(\tau)=\frac{1}{\overline{\tau}}f(\frac{\tau}{\overline{\tau}})$. The
scaling functions for both byte and packet flows obeys the same stretching
exponential form, $f(x)=A\texttt{exp}(-Bx^{\beta})$, with $\beta \approx 0.45$.
In addition, we detect a strong memory effect that a short (or long) recurrence
interval tends to be followed by another short (or long) one. The detrended
fluctuation analysis further demonstrates the presence of long-term correlation
in recurrence intervals.
