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Barrier coverage with wireless sensors
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Source International Conference on Mobile Computing and Networking archive
Proceedings of the 11th annual international conference on Mobile computing and networking table of contents
Cologne, Germany
SESSION: Sensor networks table of contents
Pages: 284 - 298  
Year of Publication: 2005
ISBN:1-59593-020-5
Authors
Santosh Kumar  Ohio State University
Ten H. Lai  Ohio State University
Anish Arora  Ohio State University
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

In old times, castles were surrounded by moats (deep trenches filled with water, and even alligators) to thwart or discourage intrusion attempts. One can now replace such barriers with stealthy and wireless sensors. In this paper, we develop theoretical foundations for laying barriers of wireless sensors. We define the notion of k-barrier coverage of a belt region using wireless sensors. We propose efficient algorithms using which one can quickly determine, after deploying the sensors, whether a region is k-barrier covered. Next, we establish the optimal deployment pattern to achieve k-barrier coverage when deploying sensors deterministically. Finally, we consider barrier coverage with high probability when sensors are deployed randomly. We introduce two notions of probabilistic barrier coverage in a belt region -- weak and strong barrier coverage. While weak barrier-coverage with high probability guarantees the detection of intruders as they cross a barrier of stealthy sensors, a sensor network providing strong barrier-coverage with high probability (at the expense of more sensors) guarantees the detection of all intruders crossing a barrier of sensors, even when the sensors are not stealthy. Both types of barrier coverage require significantly less number of sensors than full-coverage, where every point in the region needs to be covered. We derive critical conditions for weak k-barrier coverage, using which one can compute the minimum number of sensors needed to provide weak k-barrier coverage with high probability in a given belt region. Deriving critical conditions for strong k-barrier coverage for a belt region is still an open problem.


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  23

Collaborative Colleagues:
Santosh Kumar: colleagues
Ten H. Lai: colleagues
Anish Arora: colleagues