A Study of Deterministic Trends in Self-Similar Web-Cache Traffic using Wavelet Analysis
نویسنده
چکیده
A wavelet-based estimator for the analysis of self-similarity and long-range dependence is studied. The estimator is shown to be unbiased and highly robust against the presence of deterministic trends. The estimator is used to perform a thorough analysis of the self-similarity in Web-cache traffic, which is known to contain periodic trends due to usage patterns of Web users.
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