Strong barrier coverage in directional sensor networks

  • Authors:

  • Dan Tao;Shaojie Tang;Haitao Zhang;Xufei Mao;Huadong Ma

  • Affiliations:

  • School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China;Department of Computer Science, Illinois Institute of Technology, Chicago 60616, USA;Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunication, Beijing 100876, China;School of Software, TNLIST, Tsinghua University, Beijing 100084, China;Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunication, Beijing 100876, China

  • Venue:
  • Computer Communications
  • Year:
  • 2012

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Abstract

Barrier coverage is an important problem for sensor networks to fulfill some given sensing tasks. Barrier coverage guarantees the detection of events happened crossing a barrier of sensors. In majority study of barrier coverage using sensor networks, sensors are assumed to have an isotropic sensing model. However, in many applications such as monitoring an area using video camera, the sensors have directional sensing model. In this paper, we investigate strong barrier coverage using directional sensors, where sensors have arbitrarily tunable orientations to provide good coverage. We investigate the problem of finding appropriate orientations of directional sensors such that they can provide strong barrier coverage. We start with one-dimension strong barrier coverage problem, and propose a polynomial time algorithm to achieve strong barrier coverage with minimum number of required directional sensors. We further investigate the strong barrier coverage problem under two-dimensional setting, by exploiting geographical relations among directional sensors and deployment region boundaries in two-dimension plane, we introduce the concept of virtual node to reduce the solution space from continuous domain to discrete domain. Particularly, we construct a directional barrier graph (DBG) to model this barrier coverage problem such that we can quickly answer whether there exist directional sensors' orientations that can provide strong barrier coverage over a given belt region. If such orientations exist, we then develop energy-efficient solutions that will approximately minimize (1) the total and (2) the maximum rotation angles of all directional sensors. Extensive simulations are conducted to verify the effectiveness of our solution.