scholarly journals 3D Localization Algorithm Based on Voronoi Diagram and Rank Sequence in Wireless Sensor Network

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xi Yang ◽  
Fang Yan ◽  
Jun Liu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Voronoi Diagram ◽  
Optimal Parameter ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
3D Space

Accurate nodes’ localization is a key problem in wireless sensor network (WSN for short). This paper discusses and analyzes the effects of Voronoi diagram in 3D location space. Then it proposes Sequence Localization Correction algorithm based on 3D Voronoi diagram (SLC3V), which introduces 3D Voronoi diagram to divide the 3D location space and constructs the rank sequence tables of virtual beacon nodes. SLC3V uses RSSI method between beacon nodes as a reference to correct the measured distance and fixes the location sequence of unknown nodes. Next, it selects optimal parameterNand realizes the weighted location estimate withNvalid virtual beacon nodes by normalization process of rank correlation coefficients. Compared with other sequence location algorithms, simulation experiments show that it can improve the localization accuracy for nodes in complex 3D space with less measurements and computational costs.

Sequence Localization Algorithm Based on 3D Voronoi Diagram in Wireless Sensor Network

2014 ◽  
Vol 644-650 ◽  
pp. 4422-4426 ◽  
Author(s):  
Xi Yang ◽  
Jun Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Voronoi Diagram ◽  
Wireless Sensor ◽  
Weighted Estimate ◽  
Localization Algorithm ◽  
Simulation Experiments ◽  
Localization Accuracy ◽  
3D Space ◽  
Unknown Node

For nodes’ self-localization in wireless sensor networks (WSN), a new localization algorithm called Sequence Localization algorithm based on 3D Voronoi diagram (SL3V) is proposed, which uses 3D Voronoi diagram to divide the localization space.It uses the polyhedron vertices as the virtual beacon nodes and constructs the rank sequence table of virtual beacon nodes. Then it computes Kendall coefficients of the ranks in the optimal rank sequence table and that of the unknown node. Finally, it realizes the weighted estimate of the unknown node by normalization processing Kendall coefficients. Simulation experiments prove that itcan obviously improve the localization accuracy compared with the traditional 2D sequence-based localization and can satisfy the need of localization for 3D space.

scholarly journals A Hybrid Localization Approach in 3D Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Baohui Zhang ◽  
Jin Fan ◽  
Guojun Dai ◽  
Tom H. Luan
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Propagation Model ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Localization Accuracy ◽  
3D Localization ◽  
Hybrid Localization ◽  
Range Free

Location information acquisition is crucial for many wireless sensor network (WSN) applications. While existing localization approaches mainly focus on 2D plane, the emerging 3D localization brings WSNs closer to reality with much enhanced accuracy. Two types of 3D localization algorithms are mainly used in localization application: the range-based localization and the range-free localization. The range-based localization algorithm has strict requirements on hardware and therefore is costly to implement in practice. The range-free localization algorithm reduces the hardware cost but at the expense of low localization accuracy. On addressing the shortage of both algorithms, in this paper, we develop a novel hybrid localization scheme, which utilizes the range-based attribute RSSI and the range-free attribute hopsize, to achieve accurate yet low-cost 3D localization. As anchor node deployment strategy plays an important role in improving the localization accuracy, an anchor node configuration scheme is also developed in this work by utilizing the MIS (maximal independent set) of a network. With proper anchor node configuration and propagation model selection, using simulations, we show that our proposed algorithm improves the localization accuracy by 38.9% compared with 3D DV-HOP and 52.7% compared with 3D centroid.

scholarly journals An Algorithm of Mobile Robot Node Location Based on Wireless Sensor Network

2017 ◽  
Vol 13 (05) ◽  
pp. 4 ◽  
Author(s):  
Peng An
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Simulation Experiments ◽  
Localization Accuracy ◽  
Node Location ◽  
Classical Localization ◽  
Localization Precision

In the wireless sensor network, there is a consistent one-to-one match between the information collected by the node and the location of the node. Therefore, it attempts to determine the location of unknown nodes for wireless sensor networks. At present, there are many kinds of node localization methods. Because of the distance error, hardware level, application environment and application costs and other factors, the positioning accuracy of various node positioning methods is not in complete accord. The objective function is established and algorithm simulation experiments are carried out to make a mobile ronot node localization.  The experimnettal results showed that  the proposed algorithm can achieve higher localization precision in fewer nodes. In addition, the localization algorithm was compared with the classical localization algorithm. In conclusion, it is verified that the localization algorithm proposed in this paper has higher localization accuracy than the traditional classical localization algorithm when the number of nodes is larger than a certain number

Research on RSSI and Triangles Deformation Based APIT Localization Algorithm for Wireless Sensor Networks

2014 ◽  
Vol 998-999 ◽  
pp. 1305-1310
Author(s):  
Fei Liu ◽  
Guang Zeng Feng
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Localization Error ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Sparse Network ◽  
Unknown Node

The localization accuracy of traditional APIT localization algorithm for wireless sensor network depends on the Approximate Perfect Point-In-Triangulation Test (APIT), and the localization error can be promoted in sparse network. We design one improved localization algorithm (RTD-APIT) based on APIT by using the RSSI and the triangles deformation. RTD-APIT uses the RSSI to improve the APIT for achieving the preliminary location of unknown node, and expand or deform the triangles for solving the Point-In-Triangulation (PIT) problem well and enhancing the localization. Simulation shows RTD-APIT can reduce the localization error effectively, and it also promote the localization coverage.

scholarly journals A node localization algorithm based on Voronoi diagram and support vector machine for wireless sensor networks

2021 ◽  
Vol 17 (2) ◽  
pp. 155014772199341
Author(s):  
Zhanjun Hao ◽  
Jianwu Dang ◽  
Yan Yan ◽  
Xiaojuan Wang
Keyword(s):  
Support Vector Machine ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Voronoi Diagram ◽  
Wireless Sensor ◽  
Selection Strategy ◽  
Support Vector ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Scheme

For wireless sensor network, the localization algorithm based on Voronoi diagram has been applied. However, the location accuracy node position in wireless sensor network needs to be optimized by the analysis of the literature, a node location algorithm based on Voronoi diagram and support vector machine is proposed in this article. The basic idea of the algorithm is to first divide the region into several parts using Voronoi diagram and anchor node in the localization region. The range of the initial position of the target node is obtained by locating the target node in each region and then the support vector machine is used to optimize the position of the target node accurately. The localization performance of the localization algorithm is analyzed by simulation and real-world experiments. The experimental results show that the localization algorithm proposed in this article is better than the optimal region selection strategy based on Voronoi diagram-based localization scheme and Weighted Voronoi diagram-based localization scheme localization algorithms in terms of localization accuracy. Therefore, the performance of the localization algorithm proposed in this article is verified.

Enhanced the Weighted Centroid Localization Algorithm Based on Received Strength Signal in Indoor Wireless Sensor Network

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Medhav Kumar Goonjur ◽  
◽  
Irfan Dwiguna Sumitra ◽  
Sri Supatmi ◽  
◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Maximum Error ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Scheme ◽  
Indoor Wireless ◽  
Anchor Nodes ◽  
Weighted Centroid Localization

A challenging problem that arises in the Wireless Sensor Network (WSN) is localization. It is essential for applications that need information about target positions, are inside an indoor environment. The Localization scheme presented in this experiment consists of four anchor nodes that change their position coordinates and one target node that is used to control the distance. The Localization algorithm designed in this paper makes use of the combination of two algorithms; the Received Strength Signal Indication (RSSI) and Weight Centroid Localization Algorithm (WCLA), called the RSSI-WCLA algorithm. The laboratory results show that the fusion between the RSSI-WCLA algorithm is outstanding than RSSI and WCLA algorithms itself in terms of localization accuracy. However, our proposed algorithm shows that the maximum error distance is less than 0.096m.

scholarly journals Three-Dimensional Localization Algorithm Based on Improved A and DV-Hop Algorithms in Wireless Sensor Network*

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 448
Author(s):  
Xiaohu Huang ◽  
Dezhi Han ◽  
Mingming Cui ◽  
Guanghan Lin ◽  
Xinming Yin
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Large Deviation ◽  
Average Distance ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
A Algorithm ◽  
Nsga Ii ◽  
Localization Accuracy

In the traditional wireless sensor networks (WSNs) localization algorithm based on the Internet of Things (IoT), the distance vector hop (DV-Hop) localization algorithm has the disadvantages of large deviation and low accuracy in three-dimensional (3D) space. Based on the 3DDV-Hop algorithm and combined with the idea of A* algorithm, this paper proposes a wireless sensor network node location algorithm (MA*-3DDV-Hop) that integrates the improved A* algorithm and the 3DDV-Hop algorithm. In MA*-3DDV-Hop, firstly, the hop-count value of nodes is optimized and the error of average distance per hop is corrected. Then, the multi-objective optimization non dominated sorting genetic algorithm (NSGA-II) is adopted to optimize the coordinates locally. After selection, crossover, mutation, the Pareto optimal solution is obtained, which overcomes the problems of premature convergence and poor convergence of existing algorithms. Moreover, it reduces the error of coordinate calculation and raises the localization accuracy of wireless sensor network nodes. For three different multi-peak random scenes, simulation results show that MA*-3DDV-Hop algorithm has better robustness and higher localization accuracy than the 3DDV-Hop, PSO-3DDV-Hop, GA-3DDV-Hop, and N2-3DDV-Hop.

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