This paper describes how to fit fractal models, online, on IP traffic data streams. Our approach relies on maintaining a sketch of the data stream and fitting straight lines: it y...
We present deterministic sub-linear space algorithms for a number of problems over update data streams, including, estimating frequencies of items and ranges, finding approximate ...
Compressed Counting (CC) was recently proposed for approximating the th frequency moments of data streams, for 0 < 2. Under the relaxed strict-Turnstile model, CC dramaticall...
In this paper, we present a novel entropy estimator for a given set of samples drawn from an unknown probability density function (PDF). Counter to other entropy estimators, the e...
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...