scholarly journals LSRR-LA: An Anisotropy-Tolerant Localization Algorithm Based on Least Square Regularized Regression for Multi-Hop Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3974 ◽  
Author(s):  
Wei Zhao ◽  
Fei Shao ◽  
Song Ye ◽  
and Wei Zheng
Keyword(s):  
Least Square ◽  
Sensor Nodes ◽  
Localization Algorithm ◽  
Regularized Regression ◽  
Positioning Accuracy ◽  
Localization Algorithms ◽  
Geographical Distances ◽  
Localization Performance ◽  
The Given ◽  
Range Free

As is well known, multi-hop range-free localization algorithms demonstrate pretty good performance in isotropic networks in which sensor nodes distribute evenly and densely. However, these algorithms are easily affected by network topology, causing a significant decrease in positioning accuracy. To improve the localization performance in anisotropic networks, this paper presents a multi-hop range-free localization algorithm based on Least Square Regularized Regression (LSRR). By building a mapping relationship between hop counts and real distances, we can regard the process of localization as a regularized regression. Firstly, the proximity information of the given network is measured. Then, a mapping model between the geographical distances and the hop distances is constructed by LSRR. Finally, each sensor node finds its own position via this mapping. The Average Localization Error (ALE) metric is used to evaluate the proposed method in our experiments, and results show that, compared with similar methods, our approach can effectively decrease the effect of anisotropy, thus considerably improving the positioning accuracy.

Advanced Sequence-Based Localization Algorithm in Wireless Sensor Networks

2014 ◽  
Vol 651-653 ◽  
pp. 387-390 ◽  
Author(s):  
Fu Bin Zhou ◽  
Shao Li Xue
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Measuring Devices ◽  
Localization Algorithms ◽  
Positioning Algorithm ◽  
Range Free

As an important application of Internet of Things , Wireless Sensor Networks utilized in surveillance and other case.Localization of nodes in wireless sensor networks is the prerequisite and base of target tracking in some surveillance applications, so localization error of sensor nodes is a key. However, due to limited energy, unreliable link and limited communication ranges of sensor nodes, high accurate positioning is difficult to achieve, which made it hot and full of challenging for wireless sensor nodes to localize without any auxiliary facilities. Range-based localization algorithm , could achieve good accuracy but require measuring devices, thus it is not appropriate for large-scale wireless sensor networks.So range-free localization algorithms are more popular.This paper analyses the algorithms in range-free localization,and proposed Advanced Sequence-Based Localization algorithm to improve the performance of positioning algorithm in wireless sensor network.

Householder Algorithm Applied to Localization for Wireless Sensor Networks

2012 ◽  
Vol 4 (1) ◽  
pp. 18-30 ◽  
Author(s):  
Abderrahim Beni Hssane ◽  
Moulay Lahcen Hasnaoui ◽  
Said Benkirane ◽  
Driss El Ouadghiri ◽  
Mohamed Laghdir
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Least Square ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithms ◽  
Node Location ◽  
New Formula ◽  
Range Free

Many applications in Wireless Sensor Networks (WSNs) must know the position of sensor nodes in the network. That is, information from the sensors is useful only if node location information is also available. Additionally, some routing protocols use position to determine viable routes. Several localization algorithms have been proposed which can be categorized as: range-based and range-free algorithms. In this paper, the authors propose an Optimized DV-Hop (ODV-Hop), a localization range-free algorithm. The authors have used a new formula for computing the optimal hope size and used Householder algorithm for solving least square localization problem. Finally, simulation results show that the ODV-Hop achieves good location accuracy than normal DV-Hop.

Range-Free Localization Algorithm in Wireless Sensor Networks with Asymmetric Links

2013 ◽  
Vol 446-447 ◽  
pp. 1591-1595
Author(s):  
Hong Gang Zhao ◽  
Hao Shan Shi ◽  
Yong Hui Zhao
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Neighbor Discovery ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Asymmetric Links ◽  
Range Free

Good positioning accuracy and coverage are important evaluation criterion for Wireless Sensor Network localization algorithm. DV-HOP is one of the classical range-free localization algorithms, which has good adaptivity and flexibility when node density (ND) and anchor density (AD) are both smaller. However, DV-HOP doesn't consider asymmetric links' influence in heterogeneous network, which is analyzed and proved as the main reason for poor positioning accuracy in DV-HOP. Then a Range-Free Localization Algorithm in Wireless Sensor Network with Asymmetric Links (RLAAL) is proposed, whose kernel mechanisms are Neighbor Discovery Algorithm (NDA) and Least Hops Acquiring Mechanism (LHAM). Every Node uses NDA to find all neighbors and uses LHAM to find least hops to Anchor nodes. Simulation results show that RLAAL can reduce asymmetric links' influence and have better positioning accuracy and coverage than DV-HOP.

scholarly journals Localization of isotropic and anisotropic wireless sensor networks in 2D and 3D fields

2021 ◽  
Author(s):  
Soumya J. Bhat ◽  
K. V. Santhosh
Keyword(s):  
Least Squares Method ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Smart Systems ◽  
Reference Node ◽  
Accurate Localization ◽  
Localization Algorithms ◽  
Node Ratio

AbstractInternet of Things (IoT) has changed the way people live by transforming everything into smart systems. Wireless Sensor Network (WSN) forms an important part of IoT. This is a network of sensor nodes that is used in a vast range of applications. WSN is formed by the random deployment of sensor nodes in various fields of interest. The practical fields of deployment can be 2D or 3D, isotropic or anisotropic depending on the application. The localization algorithms must provide accurate localization irrespective of the type of field. In this paper, we have reported a localization algorithm called Range Reduction Based Localization (RRBL). This algorithm utilizes the properties of hop-based and centroid methods to improve the localization accuracy in various types of fields. In this algorithm, the location unknown nodes identify the close-by neighboring nodes within a predefined threshold and localize themselves by identifying and reducing the probable range of existence from these neighboring nodes. The nodes which do not have enough neighbors are localized using the least squares method. The algorithm is tested in various irregular and heterogeneous conditions. The results are compared with a few state-of-the-art hop-based and centroid-based localization techniques. RRBL has shown an improvement in localization accuracy of 28% at 10% reference node ratio and 26% at 20% reference node ratio when compared with other localization algorithms.

scholarly journals Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

2017 ◽  
Author(s):  
Junhai Luo ◽  
Liying Fan
Keyword(s):  
Sensor Networks ◽  
Time Synchronization ◽  
Sensor Nodes ◽  
Second Phase ◽  
Underwater Sensor Networks ◽  
Localization Algorithm ◽  
Two Phase ◽  
Phase Time ◽  
Anchor Nodes ◽  
Range Free

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

scholarly journals An Enhanced Hybrid 3D Localization Algorithm Based on APIT and DV-Hop

2017 ◽  
Vol 13 (09) ◽  
pp. 69 ◽  
Author(s):  
Lianjun Yi ◽  
Miaochao Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Hybrid Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
3D Localization ◽  
Localization Algorithms ◽  
Wide Range

<p>Wireless sensor networks (WSN), as a new method of information collection and processing, has a wide range of applications. Since the acquired data must be bound with the location information of sensor nodes, the sensor localization is one of the supporting technologies of wireless sensor networks. However, the common localization algorithms, such as APIT algorithm and DV-Hop algorithm, have the following problems: 1) the localization accuracy of beacon nodes is not high; 2) low coverage rate in sparse environment. In this paper, an enhanced hybrid 3D localization algorithm is designed with combining the advantages of APIT algorithm and DV-Hop algorithm. The proposed hybrid algorithm can improve the localization accuracy of the beacon nodes in dense environments by reducing the triangles in the triangle interior point test (PIT) and selecting good triangles. In addition, the algorithm can combine the advantages of APIT algorithm and DV-Hop algorithm localization algorithm to calculate the unknown node coordinates, and also improve the location coverage of the beacon nodes in sparse environment. Simulation results show that the proposed hybrid algorithm can effectively improve the localization accuracy of beacon nodes in the dense environment and the location coverage of beacon nodes in sparse environment.</p>

scholarly journals MNCE: Multi-Hop Node Localization Algorithm for Wireless Sensor Network Based on Error Correction

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 269
Author(s):  
Yinghui Meng ◽  
Yuewen Chen ◽  
Qiuwen Zhang ◽  
Weiwei Zhang
Keyword(s):  
Error Correction ◽  
Large Error ◽  
Least Square ◽  
Localization Algorithm ◽  
Target Node ◽  
Node Localization ◽  
Simulation Experiments ◽  
Connectivity Information ◽  
Localization Algorithms ◽  
Anchor Nodes

Considering the problems of large error and high localization costs of current range-free localization algorithms, a MNCE algorithm based on error correction is proposed in this study. This algorithm decomposes the multi-hop distance between nodes into several small hops. The distance of each small hop is estimated by using the connectivity information of adjacent nodes; small hops are accumulated to obtain the initial estimated distance. Then, the error-correction rate based on the error-correction concept is proposed to correct the initial estimated distance. Finally, the location of the target node is resolved by total least square methods, according to the information on the anchor nodes and estimated distances. Simulation experiments show that the MNCE algorithm is superior to the similar types of localization algorithms.

scholarly journals A Novel Method for Asynchronous Time-of-Arrival-Based Source Localization: Algorithms, Performance and Complexity

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3466
Author(s):  
Yuanpeng Chen ◽  
Zhiqiang Yao ◽  
Zheng Peng
Keyword(s):  
Source Localization ◽  
Signal Propagation ◽  
Least Square ◽  
Time Of Arrival ◽  
Propagation Time ◽  
Performance Loss ◽  
Localization Algorithms ◽  
Least Square Problem ◽  
Localization Performance ◽  
Asynchronous State

In time-of-arrival (TOA)-based source localization, accurate positioning can be achieved only when the correct signal propagation time between the source and the sensors is obtained. In practice, a clock error usually exists between the nodes causing the source and sensors to often be in an asynchronous state. This leads to the asynchronous source localization problem which is then formulated to a least square problem with nonconvex and nonsmooth objective function. The state-of-the-art algorithms need to relax the original problem to convex programming, such as semidefinite programming (SDP), which results in performance loss. In this paper, unlike the existing approaches, we propose a proximal alternating minimization positioning (PAMP) method, which minimizes the original function without relaxation. Utilizing the biconvex property of original asynchronous problem, the method divides it into two subproblems: the clock offset subproblem and the synchronous source localization subproblem. For the former we derive a global solution, whereas the later is solved by a proposed efficient subgradient algorithm extended from the simulated annealing-based Barzilai–Borwein algorithm. The proposed method obtains preferable localization performance with lower computational complexity. The convergence of our method in Lyapunov framework is also established. Simulation results demonstrate that the performance of PAMP method can be close to the optimality benchmark of Cramér–Rao Lower Bound.

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.

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