# Optimal sampling from sliding windows

@article{Braverman2012OptimalSF,
title={Optimal sampling from sliding windows},
author={Vladimir Braverman and Rafail Ostrovsky and Carlo Zaniolo},
journal={J. Comput. Syst. Sci.},
year={2012},
volume={78},
pages={260-272}
}
• Published 29 June 2009
• Computer Science
• J. Comput. Syst. Sci.
A sliding windows model is an important case of the streaming model, where only the most "recent" elements remain active and the rest are discarded in a stream. The sliding windows model is important for many applications (see, e.g., Babcock, Babu, Datar, Motwani and Widom (PODS 02); and Datar, Gionis, Indyk and Motwani (SODA 02)). There are two equally important types of the sliding windows model -- windows with fixed size, (e.g., where items arrive one at a time, and only the most recent n…
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• 2010
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This work observes that the symmetric norm streaming algorithm of Braverman et al. (STOC 2017) can be reduced to identifying and approximating the frequency of heavy-hitters in a number of substreams, and introduces a heavy-hitter algorithm that gives a (1 + )-approximation to each of the reported frequencies in the sliding window model.
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A hybrid window mechanism has been introduced in this study which can handle the most recent data stream and variable rate of data stream by sliding window and tumbling window, respectively.

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