Impact of Sensing Models on Probabilistic Blanket Coverage in Wireless Sensor Network 


Vol. 35,  No. 7, pp. 697-705, Jul.  2010


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  Abstract

In Wireless Sensor Networks (WSNs), blanket (area) coverage analysis is generally carried to find the minimum number of active sensor nodes required to cover a monitoring interest area with the desired fractional coverage-threshold. Normally, the coverage analysis is performed using the stochastic geometry as a tool. The major component of such coverage analysis is the assumed sensing model. Hence, the accuracy of such analysis depends on the underlying assumption of the sensing model: how well the assumed sensing model characterizes the real sensing phenomenon. In this paper, we review the coverage analysis for different deterministic and probabilistic sensing models like Boolean and Shadow-fading model; and extend the analysis for Exponential and hybrid Boolean-Exponential model. From the analytical performance comparison, we demonstrate the redundancy (in terms of number of sensors) that could be resulted due to the coverage analysis based on the detection capability mal-characterizing sensing models.

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  Cite this article

[IEEE Style]

S. Pudasaini, M. Kang, S. Shin, "Impact of Sensing Models on Probabilistic Blanket Coverage in Wireless Sensor Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 7, pp. 697-705, 2010. DOI: .

[ACM Style]

Subodh Pudasaini, Moonsoo Kang, and Seokjoo Shin. 2010. Impact of Sensing Models on Probabilistic Blanket Coverage in Wireless Sensor Network. The Journal of Korean Institute of Communications and Information Sciences, 35, 7, (2010), 697-705. DOI: .

[KICS Style]

Subodh Pudasaini, Moonsoo Kang, Seokjoo Shin, "Impact of Sensing Models on Probabilistic Blanket Coverage in Wireless Sensor Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 35, no. 7, pp. 697-705, 7. 2010.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880