Exposure-path prevention in directional sensor networks using sector model based percolation

Authors:
Liang Liu;Xi Zhang;Huadong Ma
Affiliations:
Networking and Information Systems Laboratory, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX;Networking and Information Systems Laboratory, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX;Beijing Key Lab of Intelligent Telecomm. Software and Multimedia, Beijing University of Posts and Telecomm., Beijing, China
Venue:
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Year:
2009

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Abstract

In wireless sensor networks, most existing works on region coverage mainly concentrate on the omnidirectional sensor based full coverage, which ensures that all points in the sensor-deployed region are covered. In contrast, this paper studies the problem of exposure-path prevention for the region coverage in directional sensor networks. Because the exposure paths are prevented as long as no moving objects or phenomena can go through a sensor-deployed region without being detected, exposure-path prevention does not require full coverage, and instead it only needs the partial coverage. Towards this end, we apply the percolation theory to solve the exposure path problem for directional sensor networks. In particular, we map the exposure path problem into a sector based percolation model, and then derive the bounds of critical density where directional sensors are deployed according to a 2-dimensional Poisson process. Also conducted is a set of extensive simulations to validate and evaluate our developed models and schemes.