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Contour map matching for event detection in sensor networks
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Source International Conference on Management of Data archive
Proceedings of the 2006 ACM SIGMOD international conference on Management of data table of contents
Chicago, IL, USA
SESSION: Sensor networks table of contents
Pages: 145 - 156  
Year of Publication: 2006
ISBN:1-59593-434-0
Authors
Wenwei Xue  Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Qiong Luo  Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Lei Chen  Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Yunhao Liu  Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Many sensor network applications, such as object tracking and disaster monitoring, require effective techniques for event detection. In this paper, we propose a novel event detection mechanism based on matching the contour maps of in-network sensory data distribution. Our key observation is that events in sensor networks can be abstracted into spatio-temporal patterns of sensory data and that pattern matching can be done efficiently through contour map matching. Therefore, we propose simple SQL extensions to allow users to specify common types of events as patterns in contour maps and study energy-efficient techniques of contour map construction and maintenance for our pattern-based event detection. Our experiments with synthetic workloads derived from a real-world coal mine surveillance application validate the effectiveness and efficiency of our approach.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  13

Collaborative Colleagues:
Wenwei Xue: colleagues
Qiong Luo: colleagues
Lei Chen: colleagues
Yunhao Liu: colleagues