NDLI: Distributed localization algorithm for wireless sensor network based on multidimensional scaling and the shortest path distance correction

Content Provider	Springer Nature Link
Author	Ding, Yingqiang Du, Liufeng Yang, Ting Sun, Yugeng
Copyright Year	2009
Abstract	Sensor localization is crucial for the configuration and applications of wireless sensor network (WSN). A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidimensional scaling (MDS) and the shortest path distance correction. In MDS-DC, several local positioning regions with reasonable distribution were firstly constructed by an adaptive search algorithm, which ensures the mergence between the local relative maps of the adjacent local position regions and can reduce the number of common nodes in the network. Then, based on the relationships between the estimated distances and actual distances of anchors, the distance estimation vectors of sensors around anchors were corrected in each local positioning region. During the computations of the local relative coordinates, an iterative process, which is the combination of classical MDS algorithm and SMACOF algorithm, was applied. Finally, the global relative positions or absolute positions of sensors were obtained through merging the relative maps of all local positioning regions. Simulation results show that MDS-DC has better performances in positioning precision, energy efficiency and robustness to range error, which can meet the requirements of applications for sensor localization in WSN.
Starting Page	237
Ending Page	244
Page Count	8
File Format	PDF
ISSN	10064982
Journal	Transactions of Tianjin University
Volume Number	15
Issue Number	4
e-ISSN	19958196
Language	English
Publisher	Tianjin University
Publisher Date	2009-09-10
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	wireless sensor network (WSN) multidimensional scaling local positioning region relative coordinates Science Mechanical Engineering
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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