کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
452182 694474 2011 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Semi-supervised Laplacian regularized least squares algorithm for localization in wireless sensor networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
Semi-supervised Laplacian regularized least squares algorithm for localization in wireless sensor networks
چکیده انگلیسی

In this paper, we propose a new approach for localization in wireless sensor networks based on semi-supervised Laplacian regularized least squares algorithm. We consider two kinds of localization data: signal strength and pair-wise distance between nodes. When nodes are close within their physical location space, their localization data vectors should be similar. We first propose a solution using the alignment criterion to learn an appropriate kernel function in terms of the similarities between anchors, and the kernel function is used to measure the similarity between pair-wise sensor nodes in the networks. We then propose a semi-supervised learning algorithm based upon manifold regularization to obtain the locations of the non-anchors. We evaluate our algorithm under various network topology, transmission range and signal noise, and analyze its performance. We also compare our approach with several existing approaches, and demonstrate the high efficiency of our proposed algorithm in terms of location estimation error.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Networks - Volume 55, Issue 10, 14 July 2011, Pages 2481–2491
نویسندگان
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