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Range counting over multidimensional data streams (2004)
| Venue: | Discrete & Computational Geometry |
| Citations: | 30 - 0 self |
BibTeX
@INPROCEEDINGS{Suri04rangecounting,
author = {Subhash Suri and Csaba D. T'oth and Yunhong Zhou},
title = {Range counting over multidimensional data streams},
booktitle = {Discrete & Computational Geometry},
year = {2004},
pages = {160--169}
}
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Abstract
\Lambda \Lambda Abstract We consider the problem of approximate range counting over streams of d-dimensional points. In the data stream model, the algorithm makes a single scan of the data, which is presented in an arbitrary order, and computes a compact summary (called a sketch). The sketch, whose size depends on the approximation parameter ", can be used to count the number of points inside a query range within additive error "n, where n is the size of the stream. We present several results, deterministic and randomized, for both rectangle and halfplane ranges. 1 Introduction Data streams have emerged as an important paradigm for processing data that arrives and needs to be processed continuously. For instance, telecom service providers routinely monitor packet flows through their networks to infer usage patterns and signs of attack, or to optimize their routing tables. Financial markets, banks, web servers, and news organizations also generate rapid and continuous data streams.
Keyphrases
range counting multidimensional data stream lambda lambda abstract single scan usage pattern routing table telecom service provider continuous data stream financial market news organization introduction data stream data stream model packet flow compact summary web server approximation parameter quot query range additive error quot arbitrary order halfplane range approximate range counting d-dimensional point important paradigm present several result
