In this paper, we will examine the problem of clustering massive domain data streams. Massive-domain data streams are those in which the number of possible domain values for each a...
Skewis prevalentin manydata sourcessuchas IP traffic streams. To continually summarize the distribution of such data, a highbiased set of quantiles (e.g., 50th, 90th and 99th perc...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
Reservoir sampling is a well-known technique for random sampling over data streams. In many streaming applications, however, an input stream may be naturally heterogeneous, i.e., c...
— The data management community has recently begun to consider declarative network routing and distributed acquisition: e.g., sensor networks that execute queries about contiguou...
Mengmeng Liu, Nicholas E. Taylor, Wenchao Zhou, Za...
Reservoir sampling is a well-known technique for sequential random sampling over data streams. Conventional reservoir sampling assumes a fixed-size reservoir. There are situation...
Mohammed Al-Kateb, Byung Suk Lee, Xiaoyang Sean Wa...