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Sensors 2017, 17(7), 1636; https://doi.org/10.3390/s17071636

Localization with Graph Diffusion Property

School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China
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Received: 10 May 2017 / Revised: 5 July 2017 / Accepted: 14 July 2017 / Published: 15 July 2017
(This article belongs to the Special Issue Mobile Sensing Applications)
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Abstract

Node localization is an essential issue in wireless sensor networks (WSNs). Many range-free localization methods have been proposed to satisfy the requirement of low-system cost. However, some range-free methods only depend on network connectivity, and others only utilize the proximity information attached in neighborhood ordering. To employ the strength of the above two aspects, this paper introduces a new metric system called Combined and Weighted Diffusion Distance (CWDD). CWDD is designed to obtain the relative distance among nodes based on both graph diffusion property and neighbor information. We implement our design by embedding CWDD into two well-known localization algorithms and evaluate it by extensive simulations. Results show that our design improves the localization performance in large scale and non-uniform sensor networks, which reduces positioning errors by as much as 26%. View Full-Text
Keywords: node localization; graph diffusion property; wireless sensor networks node localization; graph diffusion property; wireless sensor networks
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Chen, P.; Yin, Y.; Gao, S.; Niu, Q.; Gu, J. Localization with Graph Diffusion Property. Sensors 2017, 17, 1636.

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