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Differentiated surveillance for sensor networks
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Source Conference On Embedded Networked Sensor Systems archive
Proceedings of the 1st international conference on Embedded networked sensor systems table of contents
Los Angeles, California, USA
SESSION: Coverage table of contents
Pages: 51 - 62  
Year of Publication: 2003
ISBN:1-58113-707-9
Authors
Ting Yan  University of Virginia, Charlottesville, Virginia
Tian He  University of Virginia, Charlottesville, Virginia
John A. Stankovic  University of Virginia, Charlottesville, Virginia
Sponsors
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
ACM: Association for Computing Machinery
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
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ABSTRACT

For many sensor network applications such as military surveillance, it is necessary to provide full sensing coverage to a security-sensitive area while at the same time minimizing energy consumption and extending system lifetime by leveraging the redundant deployment of sensor nodes. It is also preferable for the sensor network to provide differentiated surveillance service for various target areas with different degrees of security requirements. In this paper, we propose a differentiated surveillance service for sensor networks based on an adaptable energy-efficient sensing coverage protocol. In the protocol, each node is able to dynamically decide a schedule for itself to guarantee a certain degree of coverage (DOC) with average energy consumption inversely proportional to the node density. Several optimizations and extensions are proposed to provide even better performance. Simulation shows that our protocol accomplishes differentiated surveillance with low energy consumption. It outperforms other state-of-the-art schemes by as much as 50% reduction in energy consumption and as much as 130% increase in the half-life of the network.


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  77

Collaborative Colleagues:
Ting Yan: colleagues
Tian He: colleagues
John A. Stankovic: colleagues