Article

Predictive filtering: a learning-based approach to data stream filtering

Authors:

Brian F. Cooper,

Shamkant B. NavatheAuthors Info & Claims

DMSN '04: Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004

Pages 17 - 23

https://doi.org/10.1145/1052199.1052203

Published: 01 August 2004 Publication History

Abstract

Recent years have witnessed an increasing interest in filtering of distributed data streams, such as those produced by networked sensors. The focus is to conserve bandwidth and sensor battery power by limiting the number of updates sent from the source while maintaining an acceptable approximation of the value at the sink. We propose a novel technique called Predictive Filtering. We use matching predictors at the source and the sink simultaneously to predict the next update. The update is streamed only when the difference between the actual and the predicted value at the source increases beyond a threshold. Different predictors can be plugged into our framework, and we present a comparison of the effectiveness of various predictors. Through experiments performed on a bee-motion tracking log we demonstrate the effectiveness of our algorithm in limiting the number of updates while maintaining a good approximation of the streamed data at the sink.

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Cited By

Mesin LAram SPasero E(2014)A neural data-driven approach to increase Wireless Sensor Networks' lifetime2014 World Symposium on Computer Applications & Research (WSCAR)10.1109/WSCAR.2014.6916805(1-3)Online publication date: Jan-2014
https://doi.org/10.1109/WSCAR.2014.6916805
Kleiminger WKalyvianaki EPietzuch P(2011)Balancing load in stream processing with the cloudProceedings of the 2011 IEEE 27th International Conference on Data Engineering Workshops10.1109/ICDEW.2011.5767653(16-21)Online publication date: 11-Apr-2011
https://dl.acm.org/doi/10.1109/ICDEW.2011.5767653
Matos TBrayner AMaia JShin SOssowski SSchumacher MPalakal MHung C(2010)Towards in-network data prediction in wireless sensor networksProceedings of the 2010 ACM Symposium on Applied Computing10.1145/1774088.1774210(592-596)Online publication date: 22-Mar-2010
https://dl.acm.org/doi/10.1145/1774088.1774210
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cover image ACM Other conferences

DMSN '04: Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004

August 2004

124 pages

ISBN:9781450377959

DOI:10.1145/1052199

Program Chairs:
Alexandros Labrinidis
Univeristy of Pittsburgh
,
Samuel Madden
MIT

Copyright © 2004 ACM.

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Published: 01 August 2004

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Overall Acceptance Rate 6 of 16 submissions, 38%

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Cited By

Mesin LAram SPasero E(2014)A neural data-driven approach to increase Wireless Sensor Networks' lifetime2014 World Symposium on Computer Applications & Research (WSCAR)10.1109/WSCAR.2014.6916805(1-3)Online publication date: Jan-2014
https://doi.org/10.1109/WSCAR.2014.6916805
Kleiminger WKalyvianaki EPietzuch P(2011)Balancing load in stream processing with the cloudProceedings of the 2011 IEEE 27th International Conference on Data Engineering Workshops10.1109/ICDEW.2011.5767653(16-21)Online publication date: 11-Apr-2011
https://dl.acm.org/doi/10.1109/ICDEW.2011.5767653
Matos TBrayner AMaia JShin SOssowski SSchumacher MPalakal MHung C(2010)Towards in-network data prediction in wireless sensor networksProceedings of the 2010 ACM Symposium on Applied Computing10.1145/1774088.1774210(592-596)Online publication date: 22-Mar-2010
https://dl.acm.org/doi/10.1145/1774088.1774210
Liu DLi ATian LJia YZou P(2010)Study on Cost-Sensitive Communication Models on Large-scale Monitor NetworksProceedings of the 2010 International Conference on E-Business and E-Government10.1109/ICEE.2010.539(2133-2136)Online publication date: 7-May-2010
https://dl.acm.org/doi/10.1109/ICEE.2010.539
Cordina MDebono C(2009)Maximizing the lifetime of wireless sensor networks through intelligent clustering and data reduction techniquesProceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference10.5555/1688345.1688784(2508-2513)Online publication date: 5-Apr-2009
https://dl.acm.org/doi/10.5555/1688345.1688784
Ilarri SWolfson OMena EIllarramendi ASistla P(2009)A query processor for prediction-based monitoring of data streamsProceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology10.1145/1516360.1516409(415-426)Online publication date: 24-Mar-2009
https://dl.acm.org/doi/10.1145/1516360.1516409
Cordina MDebono C(2009)Maximizing the Lifetime of Wireless Sensor Networks through Intelligent Clustering and Data Reduction Techniques2009 IEEE Wireless Communications and Networking Conference10.1109/WCNC.2009.4917803(1-6)Online publication date: Apr-2009
https://doi.org/10.1109/WCNC.2009.4917803
ZhiYong HRongHua D(2009)A Prediction Framework for Distributed Data Stream ProcessingProceedings of the 2009 Pacific-Asia Conference on Circuits, Communications and Systems10.1109/PACCS.2009.194(179-183)Online publication date: 16-May-2009
https://dl.acm.org/doi/10.1109/PACCS.2009.194
Li ATian LJia YYang S(2009)Research on Cost-Sensitive Communication Models over Distributed Data Streams ProcessingProceedings of the 2009 First International Conference on Advances in Databases, Knowledge, and Data Applications10.1109/DBKDA.2009.19(120-124)Online publication date: 1-Mar-2009
https://dl.acm.org/doi/10.1109/DBKDA.2009.19
Matos TBrayner ÂMaia Jda Silva Torres RRubira C(2008)Agregação e predição de dados em rede com precisão ajustável no processamento de consultas em redes de sensores sem fioProceedings of the 23rd Brazilian symposium on Databases10.5555/1498932.1498947(150-164)Online publication date: 13-Oct-2008
https://dl.acm.org/doi/10.5555/1498932.1498947
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