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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/6702
Title: Link-centric probabilistic coverage model for transceiver-free object detection in wireless networks
Authors: Zhang, Dian
Liu, Yunhuai
Ni, Lionel M.
Keywords: Correlations methods
Object detection
Probability
Wireless sensor networks
Transceivers
Issue Date: Jun-2010
Citation: Proceedings 2010 IEEE International Conference on Distributed Computing Systems, ICDCS 2010, 21-25 June 2010, Genoa, Italy, p. 116-125
Abstract: Sensing coverage is essential for most applications in wireless networks. In traditional coverage problem study, the disk coverage model has been widely applied because of its simplicity. Though notable recent works point out that the disk model has many critical limitations when applied in practice, few successful works have been conducted to comprehensively study the issue.Motivated by this, in this paper we propose a new coverage model called T-R model. T-R model is derived from a real application of transceiver-free object detection. Compared with the traditional disk model, T-R model is able to describe many new coverage features such as the probabilistic coverage, the link-centric coverage units and the correlations between multiple coverage units. These new capabilities make T-R model a better abstraction of individual sensors. To evaluate the performance of T-R model, we conduct comprehensive empirical studies based on a test-bed of 30 telosB nodes. Experimental results show that the T-R model can adequately describe the sensing behavior in the transceiver-free object detection applications. The average error between the model and the reality is only 8%. Moreover, T-R model presents attractive flexibility, making it more appropriate for general coverage problem studies than the transceiver-free object detection.
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URI: http://hdl.handle.net/1783.1/6702
Appears in Collections:CSE Conference Papers

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