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Sampling Based Approximate \(\tau \)-Quantile Computation Algorithm in Sensor Networks

  • Ran BiEmail author
  • Jianzhong Li
  • Hong Gao
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 501)

Abstract

A fundamental issue for detecting rare event or small probability event is to generate the description for the tail probability distribution of the sensed data. Tail quantile can effectively describe the tail probability distribution. However, most of the existing works focus on the computation of approximate quantile summary, and they are inefficient in calculating tail quantile. This paper develops an algorithm based on sampling technique for computing approximate tail quantile, such that the approximate result can satisfy the requirement of given precision. A more accurate estimator is given first. For given upper bound of relative error, this algorithm satisfies that the probability of the relative error between the exact tail quantile and the returned approximate result being larger than the specified upper bound is smaller than the given failure probability. Experiments are carried out to show the correctness and effectiveness of the proposed algorithms.

Keywords

Approximate quantile Sampling based algorithm Sensor networks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina

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