RANDOM SAMPLING ALGORITHMS FOR LANDMARK WINDOWS OVER DATA STREAMS

Zhang Longbo, Li Zhanhuai, Yu Min, Wang Yong, Jiang Yun

2006

Abstract

In many applications including sensor networks, telecommunications data management, network monitoring and financial applications, data arrives in a stream. There are growing interests in algorithms over data streams recently. This paper introduces the problem of sampling from landmark windows of recent data items from data streams and presents a random sampling algorithm for this problem. The presented algorithm, which is called SMS Algorithm, is a stratified multistage sampling algorithm for landmark window. It takes different sampling fraction in different strata of landmark window, and works even when the number of data items in the landmark window varies dramatically over time. The theoretic analysis and experiments show that the algorithm is effective and efficient for continuous data streams processing.

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Paper Citation


in Harvard Style

Longbo Z., Zhanhuai L., Min Y., Yong W. and Yun J. (2006). RANDOM SAMPLING ALGORITHMS FOR LANDMARK WINDOWS OVER DATA STREAMS . In Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-972-8865-41-2, pages 103-107. DOI: 10.5220/0002440501030107

in Bibtex Style

@conference{iceis06,
author={Zhang Longbo and Li Zhanhuai and Yu Min and Wang Yong and Jiang Yun},
title={RANDOM SAMPLING ALGORITHMS FOR LANDMARK WINDOWS OVER DATA STREAMS},
booktitle={Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2006},
pages={103-107},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002440501030107},
isbn={978-972-8865-41-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - RANDOM SAMPLING ALGORITHMS FOR LANDMARK WINDOWS OVER DATA STREAMS
SN - 978-972-8865-41-2
AU - Longbo Z.
AU - Zhanhuai L.
AU - Min Y.
AU - Yong W.
AU - Yun J.
PY - 2006
SP - 103
EP - 107
DO - 10.5220/0002440501030107