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The Research on Sensor Redepeloyment and Target Localization in 3D Wireless Sensor Networks

Author: ChaiZhiJie
Tutor: WuBo
School: Xi'an University of Electronic Science and Technology
Course: Computer Software and Theory
Keywords: Three dimensional wireless sensor networks Sensor redeployment Target localization Low energy consumption
CLC: TN929.5
Type: Master's thesis
Year: 2010
Downloads: 133
Quote: 1
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Abstract


In recent years, the advancement of low-voltage microelectronics technology, wireless communication technology and sensor technology greatly facilitated the development of wireless sensor networks which play a huge role in military reconnaissance, region detection and many other fields. In this paper, after briefly introducing wireless sensor network architecture and applications, two issues which relate closely with wireless sensor network applications are proposed. They are sensors redeployment and the target detection, localization and tracking in the network.For the problem of sensor redeployment, a distributed algorithm based on virtual forces is designed in this paper. In this algorithm, the 1-hop neighbors’repulsive force, the sensing region center’s attractive force and the boundaries’ repulsive force are defined. Then the sensor position adjustment in one progress is calculated by these forces mentioned above and the energy consumption factors. Meanwhile, the termination condition is also given in this algorithm to ensure the sensors can be redeployed to a reasonable position. Theoretical proof and simulation results show that all of the sensors which are deployed in the random district will move into sensing region and self-organize a high-coverage and bi-connected network topology with low energy consumption. And the obstacle problem can be handled perfectly.In addition, scheduling algorithms are also designed to detect, locate and track a target in the network with the anticipation of low-error and low energy consumption. By analyzing the tracking process, the dynamic sub-network conception is designed and the algorithm is divided into four processes. They are cluster head selection, target detection, target location and target tracking respectively. Theoretical proof and simulation results show that compared to the simple whole network activated and traditional fixed sub-networks, this algorithm has more efficient in target localization problem.

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