DocumentCode
2889386
Title
Exposure-Path Prevention in Directional Sensor Networks Using Sector Model Based Percolation
Author
Liu, Liang ; Zhang, Xi ; Ma, Huadong
Author_Institution
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
fYear
2009
fDate
14-18 June 2009
Firstpage
1
Lastpage
5
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.
Keywords
stochastic processes; wireless sensor networks; Poisson process; directional sensor network; exposure-path prevention; omnidirectional sensor based full coverage; sector model based percolation; wireless sensor network; Bonding; Communications Society; Information systems; Intelligent sensors; Lattices; Object detection; Sensor phenomena and characterization; Sensor systems; Telecommunications; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, 2009. ICC '09. IEEE International Conference on
Conference_Location
Dresden
ISSN
1938-1883
Print_ISBN
978-1-4244-3435-0
Electronic_ISBN
1938-1883
Type
conf
DOI
10.1109/ICC.2009.5199019
Filename
5199019
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