Sensors 2016, 16(5), 722; doi:10.3390/s16050722
Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT
Thu L. N. Nguyen
and Yoan Shin *
and Yoan Shin *
School of Electronic Engineering, Soongsil University, Seoul 156-743, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 7 January 2016 / Revised: 10 May 2016 / Accepted: 14 May 2016 / Published: 18 May 2016
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
Abstract
Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. View Full-TextKeywords:
Internet of Things; wireless sensor network; localization; Euclidean distance matrix completion; semi-definite programming; modified Newton method
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
Scifeed alert for new publications
Never miss any articles matching your research from any publisher- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Share & Cite This Article
MDPI and ACS Style
Nguyen, T.L.N.; Shin, Y. Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT. Sensors 2016, 16, 722.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.