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Surveillance using non-stealthy sensors: A new intruder model.
- Source :
- Security & Communication Networks; Nov2014, Vol. 7 Issue 11, p1900-1911, 12p
- Publication Year :
- 2014
-
Abstract
- ABSTRACT We study the problem of intruder tracking with non-stealthy sensors, i.e., sensors whose ON/OFF state can be detected by an intruder, sometimes in advance. The sensor field is assumed to be operating with a sleep schedule to conserve energy. Both motion sensors and presence sensors are considered. We provide a rigorous basis for the study of this scenario by defining a new intruder model, the Ideal Intruder, that knows the entire sleep schedule of all the sensors in the field. More realistic intruders that have spatially and temporally limited knowledge of the sensor states are also defined. We study the well-known Random Independent Sleep (RIS) scheduling scheme with a single parameter p, giving mathematical bounds for the ideal intruder's crossing time in the motion sensor case and showing that the crossing probability in the presence sensor case undergoes a sharp transition as p increases. Further, we show that non-ideal intruders perform almost as well as the ideal intruder against RIS. Motivated by this finding and by the comparison between Barrier Coverage and RIS, we define a new sleep scheduling scheme, Spotlight, that is more robust to faults than Barrier Coverage and more effective than RIS. But more than that, Spotlight is shown to be specifically suited to the non-stealthy case because a non-ideal intruder, that is, one with limited information performs significantly worse against it than the ideal intruder. Spotlight, therefore, apart from being a novel and interesting sleep scheduling scheme in its own right, also illustrates the power of the analytical framework we introduce in this paper. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19390114
- Volume :
- 7
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Security & Communication Networks
- Publication Type :
- Academic Journal
- Accession number :
- 99019770
- Full Text :
- https://doi.org/10.1002/sec.904