POT: An efficient top-k monitoring method for spatially correlated sensor readings

Yonghyun Cho, Jihoon Son, Yon Dohn Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)

Abstract

In this paper, we discuss the top-k monitoring over sensor networks. Since sensor readings are usually correlated with location, top-k nodes are clustered at some areas. Motivated by such a characteristic, we propose a novel tree structure named partial ordered tree(POT) to efficiently maintain clusters of the highest readings. By using POTs, only candidate nodes which might be included in top-k result are evaluated for query processing. Through simulation experiments, we evaluate the performance of the POT method in comparison with conventional methods.

Original languageEnglish
Title of host publication5th International Workshop on Data Management for Sensor Networks, DMSN'08, In Conjunction with the 34th International Conference on Very Large Data Bases
Pages8-13
Number of pages6
DOIs
Publication statusPublished - 2008 Dec 1
Event5th International Workshop on Data Management for Sensor Networks, DMSN'08, In Conjunction with the 34th International Conference on Very Large Data Bases - Auckland, New Zealand
Duration: 2008 Aug 242008 Aug 24

Other

Other5th International Workshop on Data Management for Sensor Networks, DMSN'08, In Conjunction with the 34th International Conference on Very Large Data Bases
CountryNew Zealand
CityAuckland
Period08/8/2408/8/24

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Keywords

  • Sensor networks
  • Top-k monitoring

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Cite this

Cho, Y., Son, J., & Chung, Y. D. (2008). POT: An efficient top-k monitoring method for spatially correlated sensor readings. In 5th International Workshop on Data Management for Sensor Networks, DMSN'08, In Conjunction with the 34th International Conference on Very Large Data Bases (pp. 8-13) https://doi.org/10.1145/1402050.1402053