Browsing by Author "Chu, Hung-Chi"

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A GPS-less, outdoor, self-positioning method for wireless sensor networks
(2007-07-01)
Chu, Hung-Chi
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Jan, Rong-Hong
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資訊工程學系
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Department of Computer Science
One challenging issue in sensor networks is to determine where a given sensor node is physically located. This problem is especially crucial for very small sensor nodes. This paper presents a GPS-less, outdoor, self-positioning method for wireless sensor networks. In our method, a set of nodes, called reference points (RPs), are deployed in the sensor network with overlapping regions of coverage. The RP periodically broadcasts beacon frames which contain localization data. The sensor node collects the beacon frames from RPs and process the data in the frame; it can then easily localize itself. The analysis of positioning accuracy is given to show how well a sensor node can correctly localize itself. In the optimal transmitting power, the worst-case accuracy for all data points is within 28.87% of the separation-distance between two adjacent RPs and the average accuracy is within 15.51%. The simulation results also show the robustness of the proposed method. Finally, we have implemented our positioning method on a sensor network test bed and the actual measurement show that the method can achieve average accuracy within 17.9% of the separation-distance between two adjacent RPs in an outdoor environment. (C) 2006 Elsevier B.V. All rights reserved.
A multiple power-level approach for wireless sensor network positioning
(2008-11-13)
Fang, Jen-Yu
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Chu, Hung-Chi
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Jan, Rong-Hong
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Yang, Wuu
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資訊工程學系
Wireless sensor networks enhance our ability to monitor the physical world. Many recent researches on wireless sensor networks have focused on aspects such as routing, node cooperation, and energy consumption. In addition to these topics, the positioning service is also an important function in sensor networks. This paper presents a multiple power-level positioning algorithm, discusses its capabilities, and evaluates its performance in various environments. The simulation results show that the proposed algorithm exhibits better accuracy than do traditional single power-level methods. In critical situations such as reference node failure, unstable radio transmission range and beacon collision, the proposed algorithm still performs well. Finally, the positioning method is implemented on a sensor network test bed, and the actual measurements show that, the average estimation error is 2.5 m when three power-levels are used and adjacent reference nodes are 12 m apart in an outdoor environment. (C) 2008 Elsevier B.V. All rights reserved.