Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking
AbstractThis work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies. View Full-Text
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Huang, P.-H.; Chen, J.-L.; Larosa, Y.T.; Chiang, T.-L. Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking. Sensors 2011, 11, 4358-4371.
Huang P-H, Chen J-L, Larosa YT, Chiang T-L. Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking. Sensors. 2011; 11(4):4358-4371.Chicago/Turabian Style
Huang, Po-Hsian; Chen, Jiann-Liang; Larosa, Yanuarius Teofilus; Chiang, Tsui-Lien. 2011. "Estimation of Distributed Fermat-Point Location for Wireless Sensor Networking." Sensors 11, no. 4: 4358-4371.