Research Article
Probabilistic Distance Estimation in Wireless Sensor Networks
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@INPROCEEDINGS{10.1007/978-3-642-29154-8_39, author={Ge Huang and Fl\^{a}via Delicato and Paulo Pires and Albert Zomaya}, title={Probabilistic Distance Estimation in Wireless Sensor Networks}, proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 7th International ICST Conference, MobiQuitous 2010, Sydeny, Australia, December 6-9, 2010, Revised Selected Papers}, proceedings_a={MOBIQUITOUS}, year={2012}, month={10}, keywords={Probability Model Estimating Distance Wireless Sensor Networks}, doi={10.1007/978-3-642-29154-8_39} }
- Ge Huang
Flávia Delicato
Paulo Pires
Albert Zomaya
Year: 2012
Probabilistic Distance Estimation in Wireless Sensor Networks
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-642-29154-8_39
Abstract
Since all anchor-based range-free localization algorithms require estimating the distance from an unknown node to an anchor node, such estimation is crucial for localizing nodes in environments as wireless sensor networks. We propose a new algorithm, named EDPM (Estimating Distance using a Probability Model), to estimate the distance from an unknown node to an anchor node. Simulation results show that EDPM reaches a slightly higher accuracy for distance estimation than the traditional algorithms for regularly shaped networks, but reveals significantly higher accuracy for irregularly shaped networks.
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