Localization from Connectivity in Wireless Sensor Networks Based on Distributed Weight-Multidimensional Scaling

2012 ◽  
Vol 220-223 ◽  
pp. 1887-1891
Author(s):  
Zhong Sheng Li ◽  
Zhi Long Shan
Keyword(s):  
Multidimensional Scaling ◽  
Wireless Sensor ◽  
Iteration Step ◽  
Localization Algorithm ◽  
Stable Convergence ◽  
Step Size ◽  
Localization Accuracy ◽  
Simulation Results ◽  
Absolute Coordinates ◽  
Function Connectivity

A localization algorithm from connectivity based on distributed weighted-multidimensional scaling (cdwMDS) algorithm is proposed in this paper. Each sensor selects a neighbor sensor adaptively, calculates the iteration step size with the average connectivity and updates the estimate location by optimizing the local cost function. Connectivity is used to determine the step size of gradient iterative optimization in this algorithm. After getting the estimated positions, a relative map is built and the absolute coordinates can be obtained. Simulation results show that this method could achieve higher localization accuracy and more stable convergence.

A Collaborative Multilateral Localization Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 303-306 ◽  
pp. 201-205
Author(s):  
Shao Ping Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node

Localization technology is one of the key supporting technologies in wireless sensor networks. In this paper, a collaborative multilateral localization algorithm is proposed to localization issues for wireless sensor networks. The algorithm applies anchor nodes within two hops to localize unknown nodes, and uses Nelder-Mead simplex optimization method to compute coordinates of the unknown nodes. If an unknown node can not be localized through two-hop anchor nodes, it is localized by anchor nodes and localized nodes within two hops through auxiliary iterative localization method. Simulation results show that the localization accuracy of this algorithm is very good, even in larger range errors.

Localization in Wireless Sensor Networks in Beacon Drifting Scenarios

2012 ◽  
Vol 562-564 ◽  
pp. 1234-1239
Author(s):  
Ming Xia ◽  
Qing Zhang Chen ◽  
Yan Jin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Probability Density ◽  
Sensor Nodes ◽  
Density Model ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Scenarios Simulation ◽  
Simulation Results

The beacon drifting problem occurs when the beacon nodes move accidentally after deployment. In this occasion, the localization results of sensor nodes in the network will be greatly affected and become inaccurate. In this paper, we present a localization algorithm in wireless sensor networks in beacon drifting scenarios. The algorithm first uses a probability density model to calculate the location reliability of each node, and in localization it will dynamically choose nodes with highest location reliabilities as beacon nodes to improve localization accuracy in beacon drifting scenarios. Simulation results show that the proposed algorithm achieves its design goals.

Improved DV-Hop Algorithm for Enhancing Localization Accuracy in WSN

2014 ◽  
Vol 543-547 ◽  
pp. 3256-3259 ◽  
Author(s):  
Da Peng Man ◽  
Guo Dong Qin ◽  
Wu Yang ◽  
Wei Wang ◽  
Shi Chang Xuan
Keyword(s):  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Localization Algorithm ◽  
Node Localization ◽  
Localization Accuracy ◽  
Global Average ◽  
Key Technologies ◽  
Simulation Results ◽  
Range Free

Node Localization technology is one of key technologies in wireless sensor network. DV-Hop localization algorithm is a kind of range-free algorithm. In this paper, an improved DV-Hop algorithm aiming to enhance localization accuracy is proposed. To enhance localization accuracy, average per-hop distance is replaced by corrected value of global average per-hop distance and global average per-hop error. When calculating hop distance, unknown nodes use corresponding average per-hop distance expression according to different hop value. Comparison with DV-Hop algorithm, simulation results show that the improved DV-Hop algorithm can reduce the localization error and enhance the accuracy of sensor nodes localization more effectively.

GTMA: Localization in Wireless Sensor Network Based a Group of Tri-Mobile Anchors

2017 ◽  
Vol 14 (1) ◽  
pp. 847-857 ◽  
Author(s):  
Bassam Gumaida ◽  
Chang Liu ◽  
Juan Luo
Keyword(s):  
High Accuracy ◽  
Outdoor Environment ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Accuracy ◽  
Mobile Anchor ◽  
Trajectory Mapping ◽  
Simulation Results ◽  
Better Than

Sensors positioning with high accuracy is a fundamental stone in Wireless Sensor Networks (WSNs). In outdoor environment which is hostile and unreachable, mobile anchors method is considered as an appropriate solution for locating unknown nodes. In this case, the key problems are the trajectory mapping and the needed number of mobile anchors. These mobile anchors should travel along the trajectory in order to determine the positions of unknown nodes with minimum localization error. In this paper, a localization algorithm named Group of Tri-Mobile Anchors (GTMA) is proposed, which is based on a group of tri-mobile anchors with adjustable square trajectory in the deployment area. The position of a target node is calculated by Trilateration. Simulation results show that the performance of the proposed algorithm GTMA is better than that of other algorithms adopted one mobile anchor, e.g., HILBERT, LMAT and SPIRAL algorithms. This is clearly evident in both the localization accuracy and trajectory planning.

The Mobile Node Localization Algorithm Based on Monte Carlo

2013 ◽  
Vol 712-715 ◽  
pp. 1847-1850
Author(s):  
Jun Gang Zheng ◽  
Cheng Dong Wu ◽  
Zhong Tang Chen
Keyword(s):  
Monte Carlo ◽  
Mobile Node ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Localization Accuracy ◽  
Monte Carlo Localization ◽  
Simulation Results ◽  
Specialized Hardware ◽  
High Node

There exist some mobile node localization algoriths in wireless sensor netwok,which require high computation and specialized hardware and high node large density of beacon nodes.The Monte Carlo localization method has been studied and an improved Monte Carlo node localization has been proposed. Predicting the trajectory of the node by interpolation and combing sampling box to sampling. The method can improve the efficiency of sampling and accuracy. The simulation results show that the method has achieved good localization accuracy.

Research and Improvement of DV-Hop Localization Algorithm for Wireless Sensor Network

2010 ◽  
Vol 44-47 ◽  
pp. 4028-4032
Author(s):  
Xue Guang Wang ◽  
Jie Ke Lin
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Wireless Sensor ◽  
Low Power Consumption ◽  
Localization Algorithm ◽  
Practical Application ◽  
Coverage Area ◽  
Localization Accuracy ◽  
Simulation Results ◽  
Average Size

Rang-free distributed localization algorithm has advantages of low power consumption, low cost etc, but it is weak in the localization accuracy, energy consumption of localization and the algorithm extend ability.That can not meet to the needs of practical application. To overcome the disadvantage of DV-Hop algorithm, in this paper, Two aspects improved algorithm are proposed based on the characteristics research of the original DV-Hop localization algorithm, which are the coverage area of beacon nodes and average size for one hop received by unknown nodes. Simulation results prove their validity and show the performance of the improvement algorithms is superior to the original DV-Hop algorithm.

Based on RSSI Ranging Technology for DV-Hop Localization Algorithm of Wireless Sensor Network

2012 ◽  
Vol 442 ◽  
pp. 360-365 ◽  
Author(s):  
Yang Jun Zhong
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Approximate Calculation ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Original Algorithm ◽  
Approximate Distance ◽  
Anchor Nodes ◽  
Simulation Results

For the DV-Hop algorithm of wireless sensor networks,there is an error arising problem that anchor nodes and location node hop distance is only an approximate calculation. A method based on the original Algorithm introducing RSSI ranging technique is proposed.Using RSSI ranging technology,we accord that if the anchor nodes is only a hop away from the location node,then decide whether using the DV-Hop algorithm to approach to the approximate distance between them. Simulation results show that the algorithm can effectively improve the error problems of calculating the hop distance between the anchor nodes and the location nodes, meanwhile improve the positioning accuracy of the node.

scholarly journals Secure and Robust 3D Localization in Wireless Sensor Networks

2019 ◽  
Vol 9 (1S) ◽  
pp. 104-111
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Malicious Nodes ◽  
3D Localization ◽  
Secure Localization ◽  
Simulation Results ◽  
Two Phases

The fundamental capacity of a sensor system is to accumulate and forward data to the destination. It is crucial to consider the area of gathered data, which is utilized to sort information that can be procured using confinement strategy as a piece of Wireless Sensor Networks (WSNs).Localization is a champion among the most basic progressions since it agreed as an essential part in various applications, e.g., target tracking. If the client can't gain the definite area information, the related applications can't be skillful. The crucial idea in most localization procedures is that some deployed nodes with known positions (e.g., GPS-equipped nodes) transmit signals with their coordinates so as to support other nodes to localize themselves. This paper mainly focuses on the algorithm that has been proposed to securely and robustly decide thelocation of a sensor node. The algorithm works in two phases namely Secure localization phase and Robust Localization phase. By "secure", we imply that malicious nodes should not effectively affect the accuracy of the localized nodes. By “robust”, we indicate that the algorithm works in a 3D environment even in the presence of malicious beacon nodes. The existing methodologies were proposed based on 2D localization; however in this work in addition to security and robustness, exact localization can be determined for 3D areas by utilizing anefficient localization algorithm. Simulation results exhibit that when compared to other existing algorithms, our proposed work performs better in terms of localization error and accuracy.

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.

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